Use of convolutional neural networks for segmenting images of roads from satellite
The article developed a technique for using convolutional neural networks for automatic segmentation of roads in images obtained from satellites with a synthesized aperture. The analysis of the subject area and the relevance of this study. The development of a neural network based on U-net was carri...
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| Vydáno v: | IOP conference series. Materials Science and Engineering Ročník 971; číslo 5; s. 52048 - 52052 |
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| Hlavní autoři: | , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
IOP Publishing
01.11.2020
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| ISSN: | 1757-8981, 1757-899X |
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| Abstract | The article developed a technique for using convolutional neural networks for automatic segmentation of roads in images obtained from satellites with a synthesized aperture. The analysis of the subject area and the relevance of this study. The development of a neural network based on U-net was carried out in Python 3x using the libraries TensorFlow, TensorBoard, Pandas, Numpy, Scipy, Matplotlib, Sklearn. The neural network was trained on a training sample of 1200 images prepared by hand marking. The accuracy of the developed model when testing on prepared samples was 68%. According to the results of the study, conclusions were drawn and prospects for further functional development of the developed tools were determined. |
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| AbstractList | The article developed a technique for using convolutional neural networks for automatic segmentation of roads in images obtained from satellites with a synthesized aperture. The analysis of the subject area and the relevance of this study. The development of a neural network based on U-net was carried out in Python 3x using the libraries TensorFlow, TensorBoard, Pandas, Numpy, Scipy, Matplotlib, Sklearn. The neural network was trained on a training sample of 1200 images prepared by hand marking. The accuracy of the developed model when testing on prepared samples was 68%. According to the results of the study, conclusions were drawn and prospects for further functional development of the developed tools were determined. |
| Author | Seliverstov, S A Naryshkin, R S Seliverstov, Ya A Kripak, M N |
| Author_xml | – sequence: 1 givenname: Ya A surname: Seliverstov fullname: Seliverstov, Ya A email: silver8yr@gmail.com organization: Laboratory of Intelligent Transport Systems, Solomenko Institute of Transport Problems of the Russian Academy of Sciences , Russia – sequence: 2 givenname: S A surname: Seliverstov fullname: Seliverstov, S A organization: Laboratory of Intelligent Transport Systems, Solomenko Institute of Transport Problems of the Russian Academy of Sciences , Russia – sequence: 3 givenname: R S surname: Naryshkin fullname: Naryshkin, R S organization: Department of Programming Technologies, Saint-Petersburg State University , Russia – sequence: 4 givenname: M N surname: Kripak fullname: Kripak, M N organization: Automobile Transport Department, Sevastopol State University , Russia |
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| Cites_doi | 10.1109/CTSYS.2017.8109528 10.1109/CTSYS.2017.8109506 10.1016/j.trpro.2017.01.006 10.1109/SCM.2017.7970626 10.1109/TGRS.2016.2645226 10.1088/1757-899X/709/3/033065 10.1016/J.TRPR0.2018.12.122 10.1117/12.2243798 10.1007/s11263-009-0275-4 10.1007/978-3-030-37436-5_30 10.1007/978-3-030-37436-5_33 |
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| References | Everingham (MSE_971_5_052048bib9) 2010; 88 Kripak (MSE_971_5_052048bib17) 2020; 709 Malygin (MSE_971_5_052048bib15); 1140 Seliverstov (MSE_971_5_052048bib12) 2017 Asaul (MSE_971_5_052048bib1) 2017; 20 Huang (MSE_971_5_052048bib5) 2017 Sherrah (MSE_971_5_052048bib6) 2016 Skorokhodov (MSE_971_5_052048bib14) 2018; 1140 Seliverstov (MSE_971_5_052048bib18) 2019; 18 Krizhevsky (MSE_971_5_052048bib3) 2012 Seliverstov (MSE_971_5_052048bib16) 2017 Geng (MSE_971_5_052048bib7) 2017; 55 Cheng (MSE_971_5_052048bib11) 2019 He (MSE_971_5_052048bib4) 2016 Seliverstov (MSE_971_5_052048bib2) 2017 Seliverstov (MSE_971_5_052048bib13) 2018; 36 Long (MSE_971_5_052048bib8) 2015 Mohammed El Amin (MSE_971_5_052048bib10) 2016 |
| References_xml | – year: 2019 ident: MSE_971_5_052048bib11 article-title: Recognizing Road From Satellite Images by Structured Neural Net-work, Neurocomputing – start-page: 211 year: 2017 ident: MSE_971_5_052048bib12 doi: 10.1109/CTSYS.2017.8109528 – start-page: 126 year: 2017 ident: MSE_971_5_052048bib16 doi: 10.1109/CTSYS.2017.8109506 – volume: 18 start-page: 354 year: 2019 ident: MSE_971_5_052048bib18 article-title: Sentiment analysis of “AUT0STRADA.INF0/RU” users’ comments publication-title: Tr. SPIIRAN – volume: 20 start-page: 25 year: 2017 ident: MSE_971_5_052048bib1 article-title: The Project of Intellectual Multimodal Transport System publication-title: Transportation Research Procedia doi: 10.1016/j.trpro.2017.01.006 – year: 2016 ident: MSE_971_5_052048bib6 article-title: Fully Convolutional Networks for Dense Semantic Labelling of High-Resolution Aerial Imagery – start-page: 489 year: 2017 ident: MSE_971_5_052048bib2 doi: 10.1109/SCM.2017.7970626 – volume: 55 start-page: 2442 year: 2017 ident: MSE_971_5_052048bib7 article-title: Deep Supervised and Contractive Neural Network for SAR Image Classification publication-title: IEEE Trans. Geosci. Remote Sens. doi: 10.1109/TGRS.2016.2645226 – start-page: 3431 year: 2015 ident: MSE_971_5_052048bib8 – volume: 709 start-page: 033065 year: 2020 ident: MSE_971_5_052048bib17 article-title: Analytical support for effective functioning of intelligent manufacturing and transport systems publication-title: IOP Conference Series: Materials Science and Engineering doi: 10.1088/1757-899X/709/3/033065 – volume: 36 start-page: 689 year: 2018 ident: MSE_971_5_052048bib13 article-title: Developing principles for building transport networks of conflict-free continuous traffic publication-title: Transportation research procedia doi: 10.1016/J.TRPR0.2018.12.122 – year: 2016 ident: MSE_971_5_052048bib10 doi: 10.1117/12.2243798 – volume: 88 start-page: 303 year: 2010 ident: MSE_971_5_052048bib9 article-title: The pascal visual object classes (VOC) challenge publication-title: Int. J. Comput. Vis. doi: 10.1007/s11263-009-0275-4 – start-page: 1097 year: 2012 ident: MSE_971_5_052048bib3 – start-page: 770 year: 2016 ident: MSE_971_5_052048bib4 – start-page: 2261 year: 2017 ident: MSE_971_5_052048bib5 – volume: 1140 start-page: 339 year: 2018 ident: MSE_971_5_052048bib14 doi: 10.1007/978-3-030-37436-5_30 – volume: 1140 start-page: 384 ident: MSE_971_5_052048bib15 doi: 10.1007/978-3-030-37436-5_33 |
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