Orientation guided anchoring for geospatial object detection from remote sensing imagery
Object detection from remote sensing imagery plays a significant role in a wide range of applications, including urban planning, intelligent transportation systems, ecology and environment analysis, etc. However, scale variations, orientation variations, illumination changes, and partial occlusions,...
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| Vydané v: | ISPRS journal of photogrammetry and remote sensing Ročník 160; s. 67 - 82 |
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| Hlavní autori: | , , , , , |
| Médium: | Journal Article |
| Jazyk: | English |
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Elsevier B.V
01.02.2020
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| ISSN: | 0924-2716, 1872-8235 |
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| Abstract | Object detection from remote sensing imagery plays a significant role in a wide range of applications, including urban planning, intelligent transportation systems, ecology and environment analysis, etc. However, scale variations, orientation variations, illumination changes, and partial occlusions, as well as image qualities, bring great challenges for accurate geospatial object detection. In this paper, we propose an efficient orientation guided anchoring based geospatial object detection network based on convolutional neural networks. To handle objects of varying sizes, the feature extraction subnetwork extracts a pyramid of semantically strong features at different scales. Based on orientation guided anchoring, the anchor generation subnetwork generates a small set of high-quality, oriented anchors as object proposals. After orientation region of interest pooling, objects of interest are detected from the object proposals through the object detection subnetwork. The proposed method has been tested on a large geospatial object detection dataset. Quantitative evaluations show that an overall completeness, correctness, quality, and F1-measure of 0.9232, 0.9648, 0.8931, and 0.9435, respectively, are obtained. In addition, the proposed method achieves a processing speed of 8 images per second on a GPU on the cloud computing platform. Comparative studies with the existing object detection methods also demonstrate the advantageous detection accuracy and computational efficiency of our proposed method. |
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| AbstractList | Object detection from remote sensing imagery plays a significant role in a wide range of applications, including urban planning, intelligent transportation systems, ecology and environment analysis, etc. However, scale variations, orientation variations, illumination changes, and partial occlusions, as well as image qualities, bring great challenges for accurate geospatial object detection. In this paper, we propose an efficient orientation guided anchoring based geospatial object detection network based on convolutional neural networks. To handle objects of varying sizes, the feature extraction subnetwork extracts a pyramid of semantically strong features at different scales. Based on orientation guided anchoring, the anchor generation subnetwork generates a small set of high-quality, oriented anchors as object proposals. After orientation region of interest pooling, objects of interest are detected from the object proposals through the object detection subnetwork. The proposed method has been tested on a large geospatial object detection dataset. Quantitative evaluations show that an overall completeness, correctness, quality, and F1-measure of 0.9232, 0.9648, 0.8931, and 0.9435, respectively, are obtained. In addition, the proposed method achieves a processing speed of 8 images per second on a GPU on the cloud computing platform. Comparative studies with the existing object detection methods also demonstrate the advantageous detection accuracy and computational efficiency of our proposed method. Object detection from remote sensing imagery plays a significant role in a wide range of applications, including urban planning, intelligent transportation systems, ecology and environment analysis, etc. However, scale variations, orientation variations, illumination changes, and partial occlusions, as well as image qualities, bring great challenges for accurate geospatial object detection. In this paper, we propose an efficient orientation guided anchoring based geospatial object detection network based on convolutional neural networks. To handle objects of varying sizes, the feature extraction subnetwork extracts a pyramid of semantically strong features at different scales. Based on orientation guided anchoring, the anchor generation subnetwork generates a small set of high-quality, oriented anchors as object proposals. After orientation region of interest pooling, objects of interest are detected from the object proposals through the object detection subnetwork. The proposed method has been tested on a large geospatial object detection dataset. Quantitative evaluations show that an overall completeness, correctness, quality, and F₁-measure of 0.9232, 0.9648, 0.8931, and 0.9435, respectively, are obtained. In addition, the proposed method achieves a processing speed of 8 images per second on a GPU on the cloud computing platform. Comparative studies with the existing object detection methods also demonstrate the advantageous detection accuracy and computational efficiency of our proposed method. |
| Author | Li, Aixia Guan, Haiyan Li, Dilong Yu, Yongtao Gu, Tiannan Tang, E. |
| Author_xml | – sequence: 1 givenname: Yongtao orcidid: 0000-0001-7204-9346 surname: Yu fullname: Yu, Yongtao email: allennessy@hyit.edu.cn organization: Faculty of Computer and Software Engineering, Huaiyin Institute of Technology, Huaian, JS 223003, China – sequence: 2 givenname: Haiyan orcidid: 0000-0003-3691-8721 surname: Guan fullname: Guan, Haiyan email: guanhy.nj@nuist.edu.cn organization: School of Remote Sensing and Geomatics Engineering, Nanjing University of Information Science and Technology, Nanjing, JS 210044, China – sequence: 3 givenname: Dilong surname: Li fullname: Li, Dilong organization: State Key Laboratory of Information Engineering in Surveying, Mapping, and Remote Sensing, Wuhan University, Wuhan, HB 430072, China – sequence: 4 givenname: Tiannan surname: Gu fullname: Gu, Tiannan organization: Faculty of Computer and Software Engineering, Huaiyin Institute of Technology, Huaian, JS 223003, China – sequence: 5 givenname: E. surname: Tang fullname: Tang, E. organization: Faculty of Computer and Software Engineering, Huaiyin Institute of Technology, Huaian, JS 223003, China – sequence: 6 givenname: Aixia surname: Li fullname: Li, Aixia organization: College of Surveying & Municipal Engineering, Zhejiang University of Water Resources and Electric Power, Hangzhou, ZJ 310018, China |
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| Cites_doi | 10.1016/j.isprsjprs.2018.08.014 10.1109/TGRS.2014.2337883 10.1109/TGRS.2016.2572736 10.1016/j.isprsjprs.2018.05.005 10.1109/LGRS.2018.2889247 10.1109/TGRS.2017.2658950 10.1109/LGRS.2017.2708722 10.1109/TGRS.2017.2716984 10.1109/LGRS.2019.2904076 10.1016/j.isprsjprs.2015.04.014 10.1109/JSTARS.2008.922318 10.1016/j.isprsjprs.2015.01.013 10.1109/TGRS.2019.2899955 10.3390/rs11030286 10.1109/TGRS.2015.2451002 10.3390/rs10030464 10.1109/TGRS.2018.2848901 10.1109/TGRS.2018.2827407 10.1109/LGRS.2017.2701902 10.1109/LGRS.2018.2829147 10.1109/TGRS.2018.2848243 10.1016/j.isprsjprs.2018.09.013 10.1109/LGRS.2015.2452962 10.1109/LGRS.2017.2699329 10.1109/ACCESS.2018.2881479 10.1109/TGRS.2014.2299540 10.1109/TGRS.2019.2900302 10.3390/rs9121312 10.1016/j.isprsjprs.2016.03.014 10.1109/JSTARS.2016.2620900 10.1109/TGRS.2012.2207123 10.1109/LGRS.2014.2360887 10.3390/rs10010131 10.1109/TGRS.2011.2166966 10.1109/JSTARS.2014.2361756 10.1109/TGRS.2017.2778300 10.3390/rs11070737 10.1109/TGRS.2014.2374218 10.3390/rs11030339 10.1109/JSTARS.2018.2793849 10.1109/LGRS.2017.2727515 10.1016/j.isprsjprs.2017.11.014 10.3390/rs10091470 10.1016/j.isprsjprs.2013.08.001 10.1109/TPAMI.2017.2750680 10.1109/LGRS.2010.2077272 10.1109/TGRS.2018.2841808 10.1109/TGRS.2013.2296782 10.1109/JSTARS.2013.2242846 10.1109/JSTARS.2015.2404578 10.1109/TGRS.2019.2897139 10.1109/TGRS.2016.2645610 10.1109/LGRS.2018.2813094 10.1016/j.neucom.2015.02.073 10.1109/TPAMI.2016.2577031 10.1109/LGRS.2018.2856921 10.1109/TGRS.2018.2790926 10.1109/LGRS.2015.2432135 10.1016/j.isprsjprs.2014.10.007 10.1016/j.isprsjprs.2018.02.014 10.3390/rs9111198 10.1109/LGRS.2018.2872355 10.1109/JSTARS.2017.2655098 10.1016/j.ins.2016.01.004 10.1016/j.isprsjprs.2018.05.021 10.3390/s19071651 |
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| Keywords | Oriented anchor Region proposal network Convolutional neural network Remote sensing imagery Object detection Orientation guided anchoring |
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| References | Li, Xu, Zhu, Ma, Tang (b0145) 2019; 16 Wan, Zheng, Huo, Fang (b0265) 2017; 14 Chen, Wang, Wen, Teng, Chen, Guan, Luo, Cao, Li (b0050) 2016; 54 Yao, Han, Guo, Bu, Liu (b0305) 2015; 164 Ok, Senaras, Yuksel (b0200) 2013; 51 Benedek, Descombes, Zerubia (b0025) 2010 Pang, Li, Shi, Xu, Feng (b0210) 2019; 57 Yuan (b0330) 2018; 40 Bai, Zhang, Zhou (b0015) 2014; 52 Cheng, Han (b0055) 2016; 117 Zhang, Sun, Wang, Fu (b0355) 2015; 99 Fan, Lu, Gong, Xie, Goodman (b0085) 2018; 11 Cheng, Han, Guo, Qian, Zhou, Yao, Hu (b0060) 2013; 85 Yu, Guan, Zai, Ji (b0320) 2016; 112 Lin, Shi, Zou (b0165) 2017; 14 Ma, Guo, Wu, Zhao, Zhang, Jiao (b0180) 2019; 11 Zhang, Guo, Zhu, Yu (b0350) 2018; 15 He, Zhang, Ren, Sun (b0110) 2016 Ren, He, Girshick, Sun (b0235) 2017; 39 Tychsen-Smith, L., Petersson, L., 2017. Improving object localization with fitness NMS and bounded IoU loss. arXiv preprint arvXiv: 1711.00164v3, pp. 1-9. Zhang, Yuan, Feng, Lu (b0365) 2019; 57 Qiu, Wen, Fan (b0225) 2017; 10 Zhang, Du, Zhang (b0345) 2015; 53 Chen, Gong, Chen, Li (b0045) 2019; 11 Lin, He, Yin, Chen (b0150) 2015; 12 Qiu, Wen, Liu, Deng, Fan (b0230) 2018; 10 Yu, Guan, Ji (b0315) 2015; 12 Zanotta, Zortea, Ferreira (b0335) 2018; 142 Lin, Dollár, Girshick, He, Hariharan, Blongie (b0155) 2016 Guo, Yang, Zhang, Hua (b0095) 2018; 10 Dai, Qi, Xiong, Li, Zhang, Hu, Wei (b0070) 2017 Zhong, Han, Zhang (b0380) 2018; 138 Zou, Shi (b0390) 2016; 54 He, Lin, Chen, Tai, Yin (b0105) 2017; 55 Xu, Zhu, Li, Feng, Ma, Che (b0285) 2018; 10 Yang, Zhuang, Bi, Shi, Xie (b0300) 2017; 14 Girshick (b0090) 2015 Yokoya, Iwasaki (b0310) 2015; 8 Bazi, Melgani (b0020) 2018; 56 Maboudi, Amini, Malihi, Hahn (b0185) 2018; 138 Craciun, Zerubia (b0065) 2013 ElMikaty, Stathaki (b0080) 2017; 55 Han, Zhang, Cheng, Guo, Ren (b0100) 2015; 53 Perrin, Descombes, Zerubia (b0220) 2004 Mou, Zhu (b0195) 2018; 65 Ren, Zhu, Xiao (b0240) 2018; 10 Hu, Li, Zhou, Yang, Peng, Xiao (b0120) 2019; 16 Peng, Jermyn, Prinet, Zerubia (b0215) 2008; 1 Lei, Fang, Huo, Li (b0125) 2012; 50 Long, Gong, Xiao, Liu (b0175) 2017; 55 Hong, Han, Kim, Lee, Kim (b0115) 2019; 19 Li, Mou, Liu, Wang, Zhu (b0140) 2018; 56 Yu, Ai, He, Yu, Zhong, Lu (b0325) 2018; 6 Ding, Zhang, Deng, Jia, Kuijper (b0075) 2018; 141 Zhang, Zhang (b0370) 2017; 10 Tuermer, Kurz, Reinartz, Stilla (b0250) 2013; 6 Cao, Wang, Li (b0040) 2016; 366 Wagner, Ferreira, Sanchez, Hirye, Zortea, Gloor, Phillips, Filho, Shimabukuro, Aragão (b0260) 2018; 145 Zhang, Zhang, Tao, Huang (b0340) 2011; 8 Wang, Bai, Wang, Zhou, Ren (b0270) 2019; 16 Yan, Wang, Yang, Diao, Sun, Li (b0290) 2019; 11 Zheng, Wang (b0375) 2015; 8 Liu, Ma, Chen (b0170) 2018; 15 Ari, Aksoy (b0010) 2014; 52 Cai, Jiang, Zhang, Yao, Nie (b0035) 2018; 15 Akçay, Aksoy (b0005) 2010 Leninisha, Vani (b0130) 2015; 102 Rishikeshan, Ramesh (b0245) 2018; 146 Cai, Jiang, Zhang, Zhao, Yao (b0030) 2017; 9 Lin, Goyal, Girshick, He, Dollár (b0160) 2017 Zhang, Tao, Zou (b0360) 2017; 14 Pan, Sayrol, Giro-i-Nieto, McGuinness, O’Connor (b0205) 2016 Xu, Xu, Wang, Yang, Pu (b0280) 2017; 9 Li, Cheng, Bu, You (b0135) 2018; 56 Yang, Chen (b0295) 2008 Wu, Hong, Tian, Chanussot, Li, Tao (b0275) 2019; 57 Zhou, Wei, Lim, Creighton, Nahavandi (b0385) 2018; 56 Manno-Kovács, Ok (b0190) 2015; 12 Ma (10.1016/j.isprsjprs.2019.12.001_b0180) 2019; 11 Zhou (10.1016/j.isprsjprs.2019.12.001_b0385) 2018; 56 Zanotta (10.1016/j.isprsjprs.2019.12.001_b0335) 2018; 142 Cheng (10.1016/j.isprsjprs.2019.12.001_b0055) 2016; 117 Yu (10.1016/j.isprsjprs.2019.12.001_b0315) 2015; 12 Pan (10.1016/j.isprsjprs.2019.12.001_b0205) 2016 Li (10.1016/j.isprsjprs.2019.12.001_b0135) 2018; 56 Zhong (10.1016/j.isprsjprs.2019.12.001_b0380) 2018; 138 Yuan (10.1016/j.isprsjprs.2019.12.001_b0330) 2018; 40 Yan (10.1016/j.isprsjprs.2019.12.001_b0290) 2019; 11 Akçay (10.1016/j.isprsjprs.2019.12.001_b0005) 2010 Wan (10.1016/j.isprsjprs.2019.12.001_b0265) 2017; 14 Cao (10.1016/j.isprsjprs.2019.12.001_b0040) 2016; 366 Dai (10.1016/j.isprsjprs.2019.12.001_b0070) 2017 Chen (10.1016/j.isprsjprs.2019.12.001_b0045) 2019; 11 Pang (10.1016/j.isprsjprs.2019.12.001_b0210) 2019; 57 Girshick (10.1016/j.isprsjprs.2019.12.001_b0090) 2015 Zheng (10.1016/j.isprsjprs.2019.12.001_b0375) 2015; 8 Wu (10.1016/j.isprsjprs.2019.12.001_b0275) 2019; 57 Hu (10.1016/j.isprsjprs.2019.12.001_b0120) 2019; 16 Li (10.1016/j.isprsjprs.2019.12.001_b0145) 2019; 16 Wang (10.1016/j.isprsjprs.2019.12.001_b0270) 2019; 16 Ren (10.1016/j.isprsjprs.2019.12.001_b0240) 2018; 10 Qiu (10.1016/j.isprsjprs.2019.12.001_b0225) 2017; 10 Leninisha (10.1016/j.isprsjprs.2019.12.001_b0130) 2015; 102 ElMikaty (10.1016/j.isprsjprs.2019.12.001_b0080) 2017; 55 Cheng (10.1016/j.isprsjprs.2019.12.001_b0060) 2013; 85 Mou (10.1016/j.isprsjprs.2019.12.001_b0195) 2018; 65 Liu (10.1016/j.isprsjprs.2019.12.001_b0170) 2018; 15 Long (10.1016/j.isprsjprs.2019.12.001_b0175) 2017; 55 Tuermer (10.1016/j.isprsjprs.2019.12.001_b0250) 2013; 6 Yang (10.1016/j.isprsjprs.2019.12.001_b0300) 2017; 14 Han (10.1016/j.isprsjprs.2019.12.001_b0100) 2015; 53 Yu (10.1016/j.isprsjprs.2019.12.001_b0325) 2018; 6 Qiu (10.1016/j.isprsjprs.2019.12.001_b0230) 2018; 10 Yu (10.1016/j.isprsjprs.2019.12.001_b0320) 2016; 112 Cai (10.1016/j.isprsjprs.2019.12.001_b0030) 2017; 9 Yang (10.1016/j.isprsjprs.2019.12.001_b0295) 2008 Lei (10.1016/j.isprsjprs.2019.12.001_b0125) 2012; 50 Manno-Kovács (10.1016/j.isprsjprs.2019.12.001_b0190) 2015; 12 Xu (10.1016/j.isprsjprs.2019.12.001_b0280) 2017; 9 Benedek (10.1016/j.isprsjprs.2019.12.001_b0025) 2010 Zhang (10.1016/j.isprsjprs.2019.12.001_b0370) 2017; 10 Guo (10.1016/j.isprsjprs.2019.12.001_b0095) 2018; 10 Bai (10.1016/j.isprsjprs.2019.12.001_b0015) 2014; 52 He (10.1016/j.isprsjprs.2019.12.001_b0105) 2017; 55 Fan (10.1016/j.isprsjprs.2019.12.001_b0085) 2018; 11 Yao (10.1016/j.isprsjprs.2019.12.001_b0305) 2015; 164 Lin (10.1016/j.isprsjprs.2019.12.001_b0165) 2017; 14 Ok (10.1016/j.isprsjprs.2019.12.001_b0200) 2013; 51 Zhang (10.1016/j.isprsjprs.2019.12.001_b0365) 2019; 57 Zou (10.1016/j.isprsjprs.2019.12.001_b0390) 2016; 54 Zhang (10.1016/j.isprsjprs.2019.12.001_b0355) 2015; 99 Ari (10.1016/j.isprsjprs.2019.12.001_b0010) 2014; 52 Peng (10.1016/j.isprsjprs.2019.12.001_b0215) 2008; 1 Ren (10.1016/j.isprsjprs.2019.12.001_b0235) 2017; 39 He (10.1016/j.isprsjprs.2019.12.001_b0110) 2016 Hong (10.1016/j.isprsjprs.2019.12.001_b0115) 2019; 19 Zhang (10.1016/j.isprsjprs.2019.12.001_b0360) 2017; 14 Rishikeshan (10.1016/j.isprsjprs.2019.12.001_b0245) 2018; 146 Wagner (10.1016/j.isprsjprs.2019.12.001_b0260) 2018; 145 Li (10.1016/j.isprsjprs.2019.12.001_b0140) 2018; 56 Lin (10.1016/j.isprsjprs.2019.12.001_b0150) 2015; 12 Yokoya (10.1016/j.isprsjprs.2019.12.001_b0310) 2015; 8 10.1016/j.isprsjprs.2019.12.001_b0255 Zhang (10.1016/j.isprsjprs.2019.12.001_b0345) 2015; 53 Zhang (10.1016/j.isprsjprs.2019.12.001_b0350) 2018; 15 Perrin (10.1016/j.isprsjprs.2019.12.001_b0220) 2004 Cai (10.1016/j.isprsjprs.2019.12.001_b0035) 2018; 15 Craciun (10.1016/j.isprsjprs.2019.12.001_b0065) 2013 Ding (10.1016/j.isprsjprs.2019.12.001_b0075) 2018; 141 Lin (10.1016/j.isprsjprs.2019.12.001_b0160) 2017 Maboudi (10.1016/j.isprsjprs.2019.12.001_b0185) 2018; 138 Xu (10.1016/j.isprsjprs.2019.12.001_b0285) 2018; 10 Zhang (10.1016/j.isprsjprs.2019.12.001_b0340) 2011; 8 Bazi (10.1016/j.isprsjprs.2019.12.001_b0020) 2018; 56 Chen (10.1016/j.isprsjprs.2019.12.001_b0050) 2016; 54 Lin (10.1016/j.isprsjprs.2019.12.001_b0155) 2016 |
| References_xml | – start-page: 1440 year: 2015 end-page: 1448 ident: b0090 article-title: Fast R-CNN publication-title: Proc. IEEE Int. Conf. Comput. Vis., Santiago, Chile – volume: 12 start-page: 746 year: 2015 end-page: 750 ident: b0150 article-title: Rotation-invariant object detection in remote sensing images based on radial-gradient angle publication-title: IEEE Geosci. Remote Sens. Lett. – volume: 8 start-page: 374 year: 2011 end-page: 378 ident: b0340 article-title: A multifeature tensor for remote-sensing target recognition publication-title: IEEE Geosci. Remote Sens. Lett. – volume: 14 start-page: 1665 year: 2017 end-page: 1669 ident: b0165 article-title: Fully convolutional network with task partitioning for inshore ship detection in optical remote sensing image publication-title: IEEE Geosci. Remote Sens. Lett. – volume: 51 start-page: 1701 year: 2013 end-page: 1717 ident: b0200 article-title: Automated detection of arbitrarily shaped buildings in complex environments from monocular VHR optical satellite imagery publication-title: IEEE Trans. Geosci. Remote Sens. – volume: 16 start-page: 1640 year: 2019 end-page: 1644 ident: b0145 article-title: Remote sensing airport detection based on end-to-end deep transferable convolutional neural networks publication-title: IEEE Geosci. Remote Sens. Lett. – volume: 6 start-page: 71122 year: 2018 end-page: 71131 ident: b0325 article-title: Ship detection in optical satellite images using Haar-like features and periphery-cropped neural networks publication-title: IEEE Access – volume: 54 start-page: 103 year: 2016 end-page: 116 ident: b0050 article-title: Vehicle detection in high-resolution aerial images via sparse representation and superpixels publication-title: IEEE Trans. Geosci. Remote Sens. – volume: 10 start-page: 1 year: 2018 end-page: 13 ident: b0240 article-title: Deformable faster R-CNN with aggregating multi-layer features for partially occluded object detection in optical remote sensing images publication-title: Remote Sens. – volume: 138 start-page: 281 year: 2018 end-page: 294 ident: b0380 article-title: Multi-class geospatial object detection based on a position-sensitive balancing framework for high spatial resolution remote sensing imagery publication-title: ISPRS J. Photogramm. Remote Sens. – volume: 10 start-page: 1 year: 2018 end-page: 23 ident: b0230 article-title: Unified partial configuration model framework for fast partially occluded object detection in high-resolution remote sensing images publication-title: Remote Sens. – volume: 11 start-page: 1 year: 2019 end-page: 17 ident: b0045 article-title: Object detection in remote sensing images based on scene-contextual feature pyramid network publication-title: Remote Sens. – start-page: 598 year: 2016 end-page: 606 ident: b0205 article-title: Shallow and deep convolutional networks for saliency prediction publication-title: Proc. IEEE Conf. Comput. Vis. Patten Recog., Las Vegas, USA – volume: 10 start-page: 1 year: 2018 end-page: 17 ident: b0285 article-title: End-to-end airport detection in remote sensing images combining cascade region proposal networks and multi-threshold detection networks publication-title: Remote Sens. – volume: 15 start-page: 937 year: 2018 end-page: 941 ident: b0170 article-title: Arbitrary-oriented ship detection framework in optical remote-sensing images publication-title: IEEE Geosci. Remote Sens. Lett. – volume: 10 start-page: 1909 year: 2017 end-page: 1925 ident: b0225 article-title: Occluded object detection in high-resolution remote sensing images using partial configuration object model publication-title: IEEE J. Sel. Topics Appl. Earth Observ. Remote Sens. – volume: 39 start-page: 1137 year: 2017 end-page: 1149 ident: b0235 article-title: Faster R-CNN: Towards real-time object detection with region proposal networks publication-title: IEEE Trans. Pattern Anal. Mach. Intell. – start-page: 85 year: 2008 end-page: 88 ident: b0295 article-title: Road and linear structure automatic extraction from remote sensing images using marked point process publication-title: Proc. Int. Workshop Edu. Tech. Train. & Geosci. Remote Sens., Shanghai, China – volume: 85 start-page: 32 year: 2013 end-page: 43 ident: b0060 article-title: Object detection in remote sensing imagery using a discriminatively trained mixture model publication-title: ISPRS J. Photogramm. Remote Sens. – volume: 11 start-page: 1 year: 2019 end-page: 22 ident: b0290 article-title: IoU-adaptive deformable R-CNN: Make full use of IoU for multi-class object detection in remote sensing imagery publication-title: Remote Sens. – volume: 57 start-page: 5535 year: 2019 end-page: 5548 ident: b0365 article-title: Hierarchical and robust convolutional neural network for very high-resolution remote sensing object detection publication-title: IEEE Trans. Geosci. Remote Sens. – volume: 15 start-page: 1095 year: 2018 end-page: 1099 ident: b0035 article-title: Online exemplar-based fully convolutional network for aircraft detection in remote sensing images publication-title: IEEE Geosci. Remote Sens. Lett. – volume: 53 start-page: 1346 year: 2015 end-page: 1354 ident: b0345 article-title: A sparse representation-based binary hypothesis model for target detection in hyperspectral images publication-title: IEEE Trans. Geosci. Remote Sens. – reference: Tychsen-Smith, L., Petersson, L., 2017. Improving object localization with fitness NMS and bounded IoU loss. arXiv preprint arvXiv: 1711.00164v3, pp. 1-9. – volume: 53 start-page: 3325 year: 2015 end-page: 3337 ident: b0100 article-title: Object detection in optical remote sensing images based on weakly supervised learning and high-level feature learning publication-title: IEEE Trans. Geosci. Remote Sens. – volume: 10 start-page: 1 year: 2018 end-page: 21 ident: b0095 article-title: Geospatial object detection in high resolution satellite images based on multi-scale convolutional neural network publication-title: Remote Sens. – volume: 56 start-page: 7147 year: 2018 end-page: 7161 ident: b0140 article-title: HSF-Net: multiscale deep feature embedding for ship detection in optical remote sensing imagery publication-title: IEEE Trans. Geosci. Remote Sens. – volume: 57 start-page: 5512 year: 2019 end-page: 5524 ident: b0210 article-title: R publication-title: IEEE Trans. Geosci. Remote Sens. – volume: 16 start-page: 310 year: 2019 end-page: 314 ident: b0270 article-title: Multiscale visual attention networks for object detection in VHR remote sensing images publication-title: IEEE Geosci. Remote Sens. Lett. – volume: 52 start-page: 6627 year: 2014 end-page: 6638 ident: b0010 article-title: Detection of compound structures using a Gaussian mixture model with spectral and spatial constraints publication-title: IEEE Trans. Geosci. Remote Sens. – volume: 19 start-page: 1 year: 2019 end-page: 16 ident: b0115 article-title: Application of deep-learning methods to bird detection using unmanned aerial vehicle imagery publication-title: Sens. – start-page: 2999 year: 2017 end-page: 3007 ident: b0160 article-title: Focal loss for dense object detection publication-title: Proc. IEEE Int. Conf. Comput. Vis., Venice, Italy – volume: 56 start-page: 3107 year: 2018 end-page: 3118 ident: b0020 article-title: Convolutional SVM networks for object detection in UAV imagery publication-title: IEEE Trans. Geosci. Remote Sens. – volume: 56 start-page: 7074 year: 2018 end-page: 7085 ident: b0385 article-title: Robust vehicle detection in aerial images using bag-of-words and orientation aware scanning publication-title: IEEE Trans. Geosci. Remote Sens. – volume: 16 start-page: 947 year: 2019 end-page: 951 ident: b0120 article-title: A sample update-based convolutional neural network framework for object detection in large-area remote sensing images publication-title: IEEE Geosci. Remote Sens. Lett. – volume: 14 start-page: 1198 year: 2017 end-page: 1202 ident: b0360 article-title: An on-road vehicle detection method for high-resolution aerial images based on local and global structure learning publication-title: IEEE Geosci. Remote Sens. Lett. – volume: 9 start-page: 1 year: 2017 end-page: 20 ident: b0030 article-title: Airport detection using end-to-end convolutional neural network with hard example mining publication-title: Remote Sens. – volume: 52 start-page: 6508 year: 2014 end-page: 6520 ident: b0015 article-title: VHR object detection based on structural feature extraction and query expansion publication-title: IEEE Trans. Geosci. Remote Sens. – volume: 6 start-page: 2327 year: 2013 end-page: 2337 ident: b0250 article-title: Airborne vehicle detection in dense urban areas using HoG features and disparity maps publication-title: IEEE J. Sel. Topics Appl. Earth Observ. Remote Sens. – volume: 50 start-page: 1206 year: 2012 end-page: 1217 ident: b0125 article-title: Rotation-invariant object detection of remotely sensed images based on Texton forest and Hough voting publication-title: IEEE Trans. Geosci. Remote Sens. – volume: 138 start-page: 151 year: 2018 end-page: 163 ident: b0185 article-title: Integrating fuzzy object based image analysis and ant colony optimization for road extraction from remotely sensed images publication-title: ISPRS J. Photogramm. Remote Sens. – start-page: 936 year: 2016 end-page: 944 ident: b0155 article-title: Feature pyramid networks for object detection publication-title: Proc. IEEE Conf. Comput. Vis. Pattern Recog., Honolulu, USA – start-page: 1932 year: 2010 end-page: 1935 ident: b0005 article-title: Building detection using directional spatial constraints publication-title: Proc. IEEE Int. Geosci. Remote Sens. Sympos., Honolulu, USA – volume: 1 start-page: 139 year: 2008 end-page: 146 ident: b0215 article-title: Incorporating generic and specific prior knowledge in a multiscale phase field model for road extraction from VHR images publication-title: IEEE J. Sel. Topics Appl. Earth Observ. Remote Sens. – volume: 14 start-page: 1116 year: 2017 end-page: 1120 ident: b0265 article-title: Affine invariant description and large-margin dimensionality reduction for target detection in optical remote sensing images publication-title: IEEE Geosci. Remote Sens. Lett. – volume: 57 start-page: 5146 year: 2019 end-page: 5158 ident: b0275 article-title: ORSIm detector: a novel object detection framework in optical remote sensing imagery using spatial-frequency channel features publication-title: IEEE Trans. Geosci. Remote Sens. – start-page: 1 year: 2017 end-page: 12 ident: b0070 publication-title: Proc. IEEE Int. Conf. Comput. Vis., Venice, Italy – volume: 102 start-page: 140 year: 2015 end-page: 147 ident: b0130 article-title: Water flow based geometric active deformable model for road network publication-title: ISPRS J. Photogramm. Remote Sens. – volume: 40 start-page: 2793 year: 2018 end-page: 2798 ident: b0330 article-title: Learning building extraction in aerial scenes with convolutional networks publication-title: IEEE Trans. Pattern Anal. Mach. Intell. – volume: 117 start-page: 11 year: 2016 end-page: 28 ident: b0055 article-title: A survey on object detection in optical remote sensing images publication-title: ISPRS J. Photogramm. Remote Sens. – volume: 14 start-page: 1293 year: 2017 end-page: 1297 ident: b0300 article-title: M-FCN: Effective fully convolutional network-based airplane detection framework publication-title: IEEE Geosci. Remote Sens. Lett. – volume: 11 start-page: 876 year: 2018 end-page: 887 ident: b0085 article-title: Automatic tobacco plant detection in UAV images via deep neural networks publication-title: IEEE J. Sel. Topics Appl. Earth Observ. Remote Sens. – start-page: 4122 year: 2013 end-page: 4125 ident: b0065 article-title: Unsupervised marked point process model for boat extraction in harbors from high resolution optical remotely sensed images publication-title: Proc. IEEE Int. Conf. Image Process., Melbourne, Australia – volume: 141 start-page: 208 year: 2018 end-page: 218 ident: b0075 article-title: A light and faster regional convolutional neural network for object detection in optical remote sensing images publication-title: ISPRS J. Photogramm. Remote Sens. – start-page: 1417 year: 2010 end-page: 1420 ident: b0025 article-title: Building detection in a single remotely sensed image with a point process of rectangles publication-title: Proc. Int. Conf. Pattern Recog., Istanbul, Turkey – volume: 55 start-page: 2486 year: 2017 end-page: 2498 ident: b0175 article-title: Accurate object localization in remote sensing images based on convolutional neural networks publication-title: IEEE Trans. Geosci. Remote Sens. – volume: 56 start-page: 2337 year: 2018 end-page: 2348 ident: b0135 article-title: Rotation-insensitive and context-augmented object detection in remote sensing images publication-title: IEEE Trans. Geosci. Remote Sens. – volume: 164 start-page: 162 year: 2015 end-page: 172 ident: b0305 article-title: A coarse-to-fine model for airport detection from remote sensing images using target-oriented visual saliency and CRF publication-title: Neurocomput. – volume: 55 start-page: 5913 year: 2017 end-page: 5924 ident: b0080 article-title: Detection of cars in high-resolution aerial images of complex urban environments publication-title: IEEE Trans. Geosci. Remote Sens. – volume: 12 start-page: 2183 year: 2015 end-page: 2187 ident: b0315 article-title: Rotation-invariant object detection in high-resolution satellite imagery using superpixel-based deep Hough forests publication-title: IEEE Geosci. Remote Sens. Lett. – volume: 54 start-page: 5832 year: 2016 end-page: 5845 ident: b0390 article-title: Ship detection in spaceborne optical image with SVD networks publication-title: IEEE Trans. Geosci. Remote Sens. – start-page: 2127 year: 2004 end-page: 2130 ident: b0220 article-title: Tree crown extraction using marked point processes publication-title: Proc. European Signal Process. Conf., Vienna, Austria – volume: 55 start-page: 3091 year: 2017 end-page: 3107 ident: b0105 article-title: Inshore ship detection in remote sensing images via weighted pose voting publication-title: IEEE Trans. Geosci. Remote Sens. – volume: 11 start-page: 1 year: 2019 end-page: 18 ident: b0180 article-title: A novel multi-model decision fusion network for object detection in remote sensing images publication-title: Remote Sens. – volume: 146 start-page: 11 year: 2018 end-page: 21 ident: b0245 article-title: An automated mathematical morphology driven algorithm for water body extraction from remote sensing images publication-title: ISPRS J. Photogramm. Remote Sens. – volume: 142 start-page: 162 year: 2018 end-page: 173 ident: b0335 article-title: A supervised approach for simultaneous segmentation and classification of remote sensing images publication-title: ISPRS J. Photogramm. Remote Sens. – volume: 15 start-page: 1745 year: 2018 end-page: 1749 ident: b0350 article-title: Toward arbitrary-oriented ship detection with rotated region proposal and discrimination networks publication-title: IEEE Geosoci. Remote Sens. Lett. – volume: 366 start-page: 177 year: 2016 end-page: 187 ident: b0040 article-title: Vehicle detection from highway satellite images via transfer learning publication-title: Info. Sci. – volume: 112 start-page: 50 year: 2016 end-page: 64 ident: b0320 article-title: Rotation-and-scale invariant airplane detection in high-resolution satellite images based on deep-Hough-forests publication-title: ISPRS J. Photogramm. Remote Sens. – start-page: 770 year: 2016 end-page: 778 ident: b0110 article-title: Deep residual learning for image recognition publication-title: Proc. IEEE Conf. Comput. Vis. Pattern Recog., Las Vegas, USA – volume: 8 start-page: 1924 year: 2015 end-page: 1935 ident: b0375 article-title: Semantic segmentation of remote sensing imagery using object-based Markov random field model with regional penalties publication-title: IEEE J. Sel. Topics Appl. Earth Observ. Remote Sens. – volume: 12 start-page: 2140 year: 2015 end-page: 2144 ident: b0190 article-title: Building detection from monocular VHR images by integrated urban area knowledge publication-title: IEEE Geosci. Remote Sens. Lett. – volume: 145 start-page: 362 year: 2018 end-page: 377 ident: b0260 article-title: Individual tree crown delineation in a highly diverse tropical forest using very high resolution satellite images publication-title: ISPRS J. Photogramm. Remote Sens. – volume: 9 start-page: 1 year: 2017 end-page: 19 ident: b0280 article-title: Deformable ConvNet with aspect ratio constrained NMS for object detection in remote sensing imagery publication-title: Remote Sens. – volume: 8 start-page: 2053 year: 2015 end-page: 2062 ident: b0310 article-title: Object detection based on sparse representation and Hough voting for optical remote sensing imagery publication-title: IEEE J. Sel. Topics Appl. Earth Observ. Remote Sens. – volume: 99 start-page: 30 year: 2015 end-page: 44 ident: b0355 article-title: A generic discriminative part-based model for geospatial object detection in optical remote sensing images publication-title: ISPRS J. Photogramm. Remote Sens. – volume: 10 start-page: 1511 year: 2017 end-page: 1524 ident: b0370 article-title: Airport detection and aircraft recognition based on two-layer saliency model in high spatial resolution remote-sensing images publication-title: IEEE J. Sel. Topics Appl. Earth Observ. Remote Sens. – volume: 65 start-page: 6699 year: 2018 end-page: 6711 ident: b0195 article-title: Vehicle instance segmentation from aerial image and video using a multitask learning residual fully convolutional network publication-title: IEEE Trans. Geosci. Remote Sens. – volume: 146 start-page: 11 year: 2018 ident: 10.1016/j.isprsjprs.2019.12.001_b0245 article-title: An automated mathematical morphology driven algorithm for water body extraction from remote sensing images publication-title: ISPRS J. Photogramm. Remote Sens. doi: 10.1016/j.isprsjprs.2018.08.014 – volume: 53 start-page: 1346 issue: 3 year: 2015 ident: 10.1016/j.isprsjprs.2019.12.001_b0345 article-title: A sparse representation-based binary hypothesis model for target detection in hyperspectral images publication-title: IEEE Trans. Geosci. Remote Sens. doi: 10.1109/TGRS.2014.2337883 – volume: 54 start-page: 5832 issue: 10 year: 2016 ident: 10.1016/j.isprsjprs.2019.12.001_b0390 article-title: Ship detection in spaceborne optical image with SVD networks publication-title: IEEE Trans. Geosci. Remote Sens. doi: 10.1109/TGRS.2016.2572736 – volume: 141 start-page: 208 year: 2018 ident: 10.1016/j.isprsjprs.2019.12.001_b0075 article-title: A light and faster regional convolutional neural network for object detection in optical remote sensing images publication-title: ISPRS J. Photogramm. Remote Sens. doi: 10.1016/j.isprsjprs.2018.05.005 – volume: 16 start-page: 947 issue: 6 year: 2019 ident: 10.1016/j.isprsjprs.2019.12.001_b0120 article-title: A sample update-based convolutional neural network framework for object detection in large-area remote sensing images publication-title: IEEE Geosci. Remote Sens. Lett. doi: 10.1109/LGRS.2018.2889247 – volume: 55 start-page: 3091 issue: 6 year: 2017 ident: 10.1016/j.isprsjprs.2019.12.001_b0105 article-title: Inshore ship detection in remote sensing images via weighted pose voting publication-title: IEEE Trans. Geosci. Remote Sens. doi: 10.1109/TGRS.2017.2658950 – volume: 14 start-page: 1293 issue: 8 year: 2017 ident: 10.1016/j.isprsjprs.2019.12.001_b0300 article-title: M-FCN: Effective fully convolutional network-based airplane detection framework publication-title: IEEE Geosci. Remote Sens. Lett. doi: 10.1109/LGRS.2017.2708722 – volume: 55 start-page: 5913 issue: 10 year: 2017 ident: 10.1016/j.isprsjprs.2019.12.001_b0080 article-title: Detection of cars in high-resolution aerial images of complex urban environments publication-title: IEEE Trans. Geosci. Remote Sens. doi: 10.1109/TGRS.2017.2716984 – volume: 16 start-page: 1640 issue: 10 year: 2019 ident: 10.1016/j.isprsjprs.2019.12.001_b0145 article-title: Remote sensing airport detection based on end-to-end deep transferable convolutional neural networks publication-title: IEEE Geosci. Remote Sens. Lett. doi: 10.1109/LGRS.2019.2904076 – volume: 112 start-page: 50 year: 2016 ident: 10.1016/j.isprsjprs.2019.12.001_b0320 article-title: Rotation-and-scale invariant airplane detection in high-resolution satellite images based on deep-Hough-forests publication-title: ISPRS J. Photogramm. Remote Sens. doi: 10.1016/j.isprsjprs.2015.04.014 – volume: 1 start-page: 139 issue: 2 year: 2008 ident: 10.1016/j.isprsjprs.2019.12.001_b0215 article-title: Incorporating generic and specific prior knowledge in a multiscale phase field model for road extraction from VHR images publication-title: IEEE J. Sel. Topics Appl. Earth Observ. Remote Sens. doi: 10.1109/JSTARS.2008.922318 – volume: 102 start-page: 140 year: 2015 ident: 10.1016/j.isprsjprs.2019.12.001_b0130 article-title: Water flow based geometric active deformable model for road network publication-title: ISPRS J. Photogramm. Remote Sens. doi: 10.1016/j.isprsjprs.2015.01.013 – volume: 57 start-page: 5512 issue: 8 year: 2019 ident: 10.1016/j.isprsjprs.2019.12.001_b0210 article-title: R2-CNN: Fast tiny object detection in large-scale remote sensing images publication-title: IEEE Trans. Geosci. Remote Sens. doi: 10.1109/TGRS.2019.2899955 – start-page: 598 year: 2016 ident: 10.1016/j.isprsjprs.2019.12.001_b0205 article-title: Shallow and deep convolutional networks for saliency prediction – volume: 11 start-page: 1 issue: 3 year: 2019 ident: 10.1016/j.isprsjprs.2019.12.001_b0290 article-title: IoU-adaptive deformable R-CNN: Make full use of IoU for multi-class object detection in remote sensing imagery publication-title: Remote Sens. doi: 10.3390/rs11030286 – volume: 54 start-page: 103 issue: 1 year: 2016 ident: 10.1016/j.isprsjprs.2019.12.001_b0050 article-title: Vehicle detection in high-resolution aerial images via sparse representation and superpixels publication-title: IEEE Trans. Geosci. Remote Sens. doi: 10.1109/TGRS.2015.2451002 – volume: 10 start-page: 1 issue: 3 year: 2018 ident: 10.1016/j.isprsjprs.2019.12.001_b0230 article-title: Unified partial configuration model framework for fast partially occluded object detection in high-resolution remote sensing images publication-title: Remote Sens. doi: 10.3390/rs10030464 – volume: 56 start-page: 7147 issue: 12 year: 2018 ident: 10.1016/j.isprsjprs.2019.12.001_b0140 article-title: HSF-Net: multiscale deep feature embedding for ship detection in optical remote sensing imagery publication-title: IEEE Trans. Geosci. Remote Sens. doi: 10.1109/TGRS.2018.2848901 – volume: 10 start-page: 1 issue: 10 year: 2018 ident: 10.1016/j.isprsjprs.2019.12.001_b0285 article-title: End-to-end airport detection in remote sensing images combining cascade region proposal networks and multi-threshold detection networks publication-title: Remote Sens. doi: 10.1109/TGRS.2018.2827407 – volume: 14 start-page: 1198 issue: 8 year: 2017 ident: 10.1016/j.isprsjprs.2019.12.001_b0360 article-title: An on-road vehicle detection method for high-resolution aerial images based on local and global structure learning publication-title: IEEE Geosci. Remote Sens. Lett. doi: 10.1109/LGRS.2017.2701902 – volume: 15 start-page: 1095 issue: 7 year: 2018 ident: 10.1016/j.isprsjprs.2019.12.001_b0035 article-title: Online exemplar-based fully convolutional network for aircraft detection in remote sensing images publication-title: IEEE Geosci. Remote Sens. Lett. doi: 10.1109/LGRS.2018.2829147 – volume: 56 start-page: 7074 issue: 12 year: 2018 ident: 10.1016/j.isprsjprs.2019.12.001_b0385 article-title: Robust vehicle detection in aerial images using bag-of-words and orientation aware scanning publication-title: IEEE Trans. Geosci. Remote Sens. doi: 10.1109/TGRS.2018.2848243 – volume: 145 start-page: 362 year: 2018 ident: 10.1016/j.isprsjprs.2019.12.001_b0260 article-title: Individual tree crown delineation in a highly diverse tropical forest using very high resolution satellite images publication-title: ISPRS J. Photogramm. Remote Sens. doi: 10.1016/j.isprsjprs.2018.09.013 – volume: 12 start-page: 2140 issue: 10 year: 2015 ident: 10.1016/j.isprsjprs.2019.12.001_b0190 article-title: Building detection from monocular VHR images by integrated urban area knowledge publication-title: IEEE Geosci. Remote Sens. Lett. doi: 10.1109/LGRS.2015.2452962 – volume: 14 start-page: 1116 issue: 7 year: 2017 ident: 10.1016/j.isprsjprs.2019.12.001_b0265 article-title: Affine invariant description and large-margin dimensionality reduction for target detection in optical remote sensing images publication-title: IEEE Geosci. Remote Sens. Lett. doi: 10.1109/LGRS.2017.2699329 – volume: 6 start-page: 71122 year: 2018 ident: 10.1016/j.isprsjprs.2019.12.001_b0325 article-title: Ship detection in optical satellite images using Haar-like features and periphery-cropped neural networks publication-title: IEEE Access doi: 10.1109/ACCESS.2018.2881479 – volume: 52 start-page: 6627 issue: 10 year: 2014 ident: 10.1016/j.isprsjprs.2019.12.001_b0010 article-title: Detection of compound structures using a Gaussian mixture model with spectral and spatial constraints publication-title: IEEE Trans. Geosci. Remote Sens. doi: 10.1109/TGRS.2014.2299540 – volume: 57 start-page: 5535 issue: 8 year: 2019 ident: 10.1016/j.isprsjprs.2019.12.001_b0365 article-title: Hierarchical and robust convolutional neural network for very high-resolution remote sensing object detection publication-title: IEEE Trans. Geosci. Remote Sens. doi: 10.1109/TGRS.2019.2900302 – ident: 10.1016/j.isprsjprs.2019.12.001_b0255 – volume: 9 start-page: 1 issue: 12 year: 2017 ident: 10.1016/j.isprsjprs.2019.12.001_b0280 article-title: Deformable ConvNet with aspect ratio constrained NMS for object detection in remote sensing imagery publication-title: Remote Sens. doi: 10.3390/rs9121312 – start-page: 1417 year: 2010 ident: 10.1016/j.isprsjprs.2019.12.001_b0025 article-title: Building detection in a single remotely sensed image with a point process of rectangles – volume: 117 start-page: 11 year: 2016 ident: 10.1016/j.isprsjprs.2019.12.001_b0055 article-title: A survey on object detection in optical remote sensing images publication-title: ISPRS J. Photogramm. Remote Sens. doi: 10.1016/j.isprsjprs.2016.03.014 – volume: 10 start-page: 1511 issue: 4 year: 2017 ident: 10.1016/j.isprsjprs.2019.12.001_b0370 article-title: Airport detection and aircraft recognition based on two-layer saliency model in high spatial resolution remote-sensing images publication-title: IEEE J. Sel. Topics Appl. Earth Observ. Remote Sens. doi: 10.1109/JSTARS.2016.2620900 – volume: 51 start-page: 1701 issue: 3 year: 2013 ident: 10.1016/j.isprsjprs.2019.12.001_b0200 article-title: Automated detection of arbitrarily shaped buildings in complex environments from monocular VHR optical satellite imagery publication-title: IEEE Trans. Geosci. Remote Sens. doi: 10.1109/TGRS.2012.2207123 – volume: 12 start-page: 746 issue: 4 year: 2015 ident: 10.1016/j.isprsjprs.2019.12.001_b0150 article-title: Rotation-invariant object detection in remote sensing images based on radial-gradient angle publication-title: IEEE Geosci. Remote Sens. Lett. doi: 10.1109/LGRS.2014.2360887 – volume: 10 start-page: 1 issue: 1 year: 2018 ident: 10.1016/j.isprsjprs.2019.12.001_b0095 article-title: Geospatial object detection in high resolution satellite images based on multi-scale convolutional neural network publication-title: Remote Sens. doi: 10.3390/rs10010131 – volume: 50 start-page: 1206 issue: 4 year: 2012 ident: 10.1016/j.isprsjprs.2019.12.001_b0125 article-title: Rotation-invariant object detection of remotely sensed images based on Texton forest and Hough voting publication-title: IEEE Trans. Geosci. Remote Sens. doi: 10.1109/TGRS.2011.2166966 – volume: 8 start-page: 1924 issue: 5 year: 2015 ident: 10.1016/j.isprsjprs.2019.12.001_b0375 article-title: Semantic segmentation of remote sensing imagery using object-based Markov random field model with regional penalties publication-title: IEEE J. Sel. Topics Appl. Earth Observ. Remote Sens. doi: 10.1109/JSTARS.2014.2361756 – start-page: 2127 year: 2004 ident: 10.1016/j.isprsjprs.2019.12.001_b0220 article-title: Tree crown extraction using marked point processes – volume: 56 start-page: 2337 issue: 4 year: 2018 ident: 10.1016/j.isprsjprs.2019.12.001_b0135 article-title: Rotation-insensitive and context-augmented object detection in remote sensing images publication-title: IEEE Trans. Geosci. Remote Sens. doi: 10.1109/TGRS.2017.2778300 – volume: 11 start-page: 1 issue: 7 year: 2019 ident: 10.1016/j.isprsjprs.2019.12.001_b0180 article-title: A novel multi-model decision fusion network for object detection in remote sensing images publication-title: Remote Sens. doi: 10.3390/rs11070737 – start-page: 1932 year: 2010 ident: 10.1016/j.isprsjprs.2019.12.001_b0005 article-title: Building detection using directional spatial constraints – volume: 53 start-page: 3325 issue: 6 year: 2015 ident: 10.1016/j.isprsjprs.2019.12.001_b0100 article-title: Object detection in optical remote sensing images based on weakly supervised learning and high-level feature learning publication-title: IEEE Trans. Geosci. Remote Sens. doi: 10.1109/TGRS.2014.2374218 – volume: 11 start-page: 1 issue: 3 year: 2019 ident: 10.1016/j.isprsjprs.2019.12.001_b0045 article-title: Object detection in remote sensing images based on scene-contextual feature pyramid network publication-title: Remote Sens. doi: 10.3390/rs11030339 – start-page: 4122 year: 2013 ident: 10.1016/j.isprsjprs.2019.12.001_b0065 article-title: Unsupervised marked point process model for boat extraction in harbors from high resolution optical remotely sensed images – volume: 11 start-page: 876 issue: 3 year: 2018 ident: 10.1016/j.isprsjprs.2019.12.001_b0085 article-title: Automatic tobacco plant detection in UAV images via deep neural networks publication-title: IEEE J. Sel. Topics Appl. Earth Observ. Remote Sens. doi: 10.1109/JSTARS.2018.2793849 – volume: 14 start-page: 1665 issue: 10 year: 2017 ident: 10.1016/j.isprsjprs.2019.12.001_b0165 article-title: Fully convolutional network with task partitioning for inshore ship detection in optical remote sensing image publication-title: IEEE Geosci. Remote Sens. Lett. doi: 10.1109/LGRS.2017.2727515 – volume: 138 start-page: 151 year: 2018 ident: 10.1016/j.isprsjprs.2019.12.001_b0185 article-title: Integrating fuzzy object based image analysis and ant colony optimization for road extraction from remotely sensed images publication-title: ISPRS J. Photogramm. Remote Sens. doi: 10.1016/j.isprsjprs.2017.11.014 – volume: 10 start-page: 1 issue: 9 year: 2018 ident: 10.1016/j.isprsjprs.2019.12.001_b0240 article-title: Deformable faster R-CNN with aggregating multi-layer features for partially occluded object detection in optical remote sensing images publication-title: Remote Sens. doi: 10.3390/rs10091470 – volume: 85 start-page: 32 year: 2013 ident: 10.1016/j.isprsjprs.2019.12.001_b0060 article-title: Object detection in remote sensing imagery using a discriminatively trained mixture model publication-title: ISPRS J. Photogramm. Remote Sens. doi: 10.1016/j.isprsjprs.2013.08.001 – volume: 40 start-page: 2793 issue: 11 year: 2018 ident: 10.1016/j.isprsjprs.2019.12.001_b0330 article-title: Learning building extraction in aerial scenes with convolutional networks publication-title: IEEE Trans. Pattern Anal. Mach. Intell. doi: 10.1109/TPAMI.2017.2750680 – volume: 8 start-page: 374 issue: 2 year: 2011 ident: 10.1016/j.isprsjprs.2019.12.001_b0340 article-title: A multifeature tensor for remote-sensing target recognition publication-title: IEEE Geosci. Remote Sens. Lett. doi: 10.1109/LGRS.2010.2077272 – start-page: 1440 year: 2015 ident: 10.1016/j.isprsjprs.2019.12.001_b0090 article-title: Fast R-CNN – volume: 65 start-page: 6699 issue: 1 year: 2018 ident: 10.1016/j.isprsjprs.2019.12.001_b0195 article-title: Vehicle instance segmentation from aerial image and video using a multitask learning residual fully convolutional network publication-title: IEEE Trans. Geosci. Remote Sens. doi: 10.1109/TGRS.2018.2841808 – volume: 52 start-page: 6508 issue: 10 year: 2014 ident: 10.1016/j.isprsjprs.2019.12.001_b0015 article-title: VHR object detection based on structural feature extraction and query expansion publication-title: IEEE Trans. Geosci. Remote Sens. doi: 10.1109/TGRS.2013.2296782 – volume: 6 start-page: 2327 issue: 6 year: 2013 ident: 10.1016/j.isprsjprs.2019.12.001_b0250 article-title: Airborne vehicle detection in dense urban areas using HoG features and disparity maps publication-title: IEEE J. Sel. Topics Appl. Earth Observ. Remote Sens. doi: 10.1109/JSTARS.2013.2242846 – start-page: 85 year: 2008 ident: 10.1016/j.isprsjprs.2019.12.001_b0295 article-title: Road and linear structure automatic extraction from remote sensing images using marked point process – volume: 8 start-page: 2053 issue: 5 year: 2015 ident: 10.1016/j.isprsjprs.2019.12.001_b0310 article-title: Object detection based on sparse representation and Hough voting for optical remote sensing imagery publication-title: IEEE J. Sel. Topics Appl. Earth Observ. Remote Sens. doi: 10.1109/JSTARS.2015.2404578 – volume: 57 start-page: 5146 issue: 7 year: 2019 ident: 10.1016/j.isprsjprs.2019.12.001_b0275 article-title: ORSIm detector: a novel object detection framework in optical remote sensing imagery using spatial-frequency channel features publication-title: IEEE Trans. Geosci. Remote Sens. doi: 10.1109/TGRS.2019.2897139 – start-page: 2999 year: 2017 ident: 10.1016/j.isprsjprs.2019.12.001_b0160 article-title: Focal loss for dense object detection – volume: 55 start-page: 2486 issue: 5 year: 2017 ident: 10.1016/j.isprsjprs.2019.12.001_b0175 article-title: Accurate object localization in remote sensing images based on convolutional neural networks publication-title: IEEE Trans. Geosci. Remote Sens. doi: 10.1109/TGRS.2016.2645610 – volume: 15 start-page: 937 issue: 6 year: 2018 ident: 10.1016/j.isprsjprs.2019.12.001_b0170 article-title: Arbitrary-oriented ship detection framework in optical remote-sensing images publication-title: IEEE Geosci. Remote Sens. Lett. doi: 10.1109/LGRS.2018.2813094 – volume: 164 start-page: 162 year: 2015 ident: 10.1016/j.isprsjprs.2019.12.001_b0305 article-title: A coarse-to-fine model for airport detection from remote sensing images using target-oriented visual saliency and CRF publication-title: Neurocomput. doi: 10.1016/j.neucom.2015.02.073 – start-page: 770 year: 2016 ident: 10.1016/j.isprsjprs.2019.12.001_b0110 article-title: Deep residual learning for image recognition – volume: 39 start-page: 1137 issue: 6 year: 2017 ident: 10.1016/j.isprsjprs.2019.12.001_b0235 article-title: Faster R-CNN: Towards real-time object detection with region proposal networks publication-title: IEEE Trans. Pattern Anal. Mach. Intell. doi: 10.1109/TPAMI.2016.2577031 – volume: 15 start-page: 1745 issue: 11 year: 2018 ident: 10.1016/j.isprsjprs.2019.12.001_b0350 article-title: Toward arbitrary-oriented ship detection with rotated region proposal and discrimination networks publication-title: IEEE Geosoci. Remote Sens. Lett. doi: 10.1109/LGRS.2018.2856921 – volume: 56 start-page: 3107 issue: 6 year: 2018 ident: 10.1016/j.isprsjprs.2019.12.001_b0020 article-title: Convolutional SVM networks for object detection in UAV imagery publication-title: IEEE Trans. Geosci. Remote Sens. doi: 10.1109/TGRS.2018.2790926 – start-page: 936 year: 2016 ident: 10.1016/j.isprsjprs.2019.12.001_b0155 article-title: Feature pyramid networks for object detection – volume: 12 start-page: 2183 issue: 11 year: 2015 ident: 10.1016/j.isprsjprs.2019.12.001_b0315 article-title: Rotation-invariant object detection in high-resolution satellite imagery using superpixel-based deep Hough forests publication-title: IEEE Geosci. Remote Sens. Lett. doi: 10.1109/LGRS.2015.2432135 – volume: 99 start-page: 30 year: 2015 ident: 10.1016/j.isprsjprs.2019.12.001_b0355 article-title: A generic discriminative part-based model for geospatial object detection in optical remote sensing images publication-title: ISPRS J. Photogramm. Remote Sens. doi: 10.1016/j.isprsjprs.2014.10.007 – volume: 138 start-page: 281 year: 2018 ident: 10.1016/j.isprsjprs.2019.12.001_b0380 article-title: Multi-class geospatial object detection based on a position-sensitive balancing framework for high spatial resolution remote sensing imagery publication-title: ISPRS J. Photogramm. Remote Sens. doi: 10.1016/j.isprsjprs.2018.02.014 – start-page: 1 year: 2017 ident: 10.1016/j.isprsjprs.2019.12.001_b0070 publication-title: Proc. IEEE Int. Conf. Comput. Vis., Venice, Italy – volume: 9 start-page: 1 issue: 11 year: 2017 ident: 10.1016/j.isprsjprs.2019.12.001_b0030 article-title: Airport detection using end-to-end convolutional neural network with hard example mining publication-title: Remote Sens. doi: 10.3390/rs9111198 – volume: 16 start-page: 310 issue: 2 year: 2019 ident: 10.1016/j.isprsjprs.2019.12.001_b0270 article-title: Multiscale visual attention networks for object detection in VHR remote sensing images publication-title: IEEE Geosci. Remote Sens. Lett. doi: 10.1109/LGRS.2018.2872355 – volume: 10 start-page: 1909 issue: 5 year: 2017 ident: 10.1016/j.isprsjprs.2019.12.001_b0225 article-title: Occluded object detection in high-resolution remote sensing images using partial configuration object model publication-title: IEEE J. Sel. Topics Appl. Earth Observ. Remote Sens. doi: 10.1109/JSTARS.2017.2655098 – volume: 366 start-page: 177 year: 2016 ident: 10.1016/j.isprsjprs.2019.12.001_b0040 article-title: Vehicle detection from highway satellite images via transfer learning publication-title: Info. Sci. doi: 10.1016/j.ins.2016.01.004 – volume: 142 start-page: 162 year: 2018 ident: 10.1016/j.isprsjprs.2019.12.001_b0335 article-title: A supervised approach for simultaneous segmentation and classification of remote sensing images publication-title: ISPRS J. Photogramm. Remote Sens. doi: 10.1016/j.isprsjprs.2018.05.021 – volume: 19 start-page: 1 issue: 7 year: 2019 ident: 10.1016/j.isprsjprs.2019.12.001_b0115 article-title: Application of deep-learning methods to bird detection using unmanned aerial vehicle imagery publication-title: Sens. doi: 10.3390/s19071651 |
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