Evolutionary computation-based self-supervised learning for image processing: a big data-driven approach to feature extraction and fusion for multispectral object detection

The image object recognition and detection technology are widely used in many scenarios. In recent years, big data has become increasingly abundant, and big data-driven artificial intelligence models have attracted more and more attention. Evolutionary computation has also provided a powerful drivin...

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Published in:	Journal of big data Vol. 11; no. 1; pp. 130 - 20
Main Authors:	Shen, Xiaoyang, Li, Haibin, Shankar, Achyut, Viriyasitavat, Wattana, Chamola, Vinay
Format:	Journal Article
Language:	English
Published:	Cham Springer International Publishing 01.12.2024 Springer Nature B.V SpringerOpen
Subjects:	Artificial intelligence Big Data Communications Engineering Computation Computational Science and Engineering Computer Science Data integration Data Mining and Knowledge Discovery Data processing Database Management Deep learning Evolutionary algorithms Evolutionary computation Extraction Feature extraction Feature recognition Image enhancement Image processing Imagery Information Storage and Retrieval Infrared imagery Learning Machine learning Mathematical Applications in Computer Science Networks Object detection Object recognition Optimization Parameter identification Self-supervised learning Target detection Big data Image processing Evolutionary computation Self-supervised learning Object detection
ISSN:	2196-1115, 2196-1115
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Abstract	The image object recognition and detection technology are widely used in many scenarios. In recent years, big data has become increasingly abundant, and big data-driven artificial intelligence models have attracted more and more attention. Evolutionary computation has also provided a powerful driving force for the optimization and improvement of deep learning models. In this paper, we propose an image object detection method based on self-supervised and data-driven learning. Differ from other methods, our approach stands out due to its innovative use of multispectral data fusion and evolutionary computation for model optimization. Specifically, our method uniquely combines visible light images and infrared images to detect and identify image targets. Firstly, we utilize a self-supervised learning method and the AutoEncoder model to perform high-dimensional feature extraction on the two types of images. Secondly, we fuse the extracted features from the visible light and infrared images to detect and identify objects. Thirdly, we introduce a model parameter optimization method using evolutionary learning algorithms to enhance model performance. Validation on public datasets shows that our method achieves comparable or superior performance to existing methods.
AbstractList	Abstract The image object recognition and detection technology are widely used in many scenarios. In recent years, big data has become increasingly abundant, and big data-driven artificial intelligence models have attracted more and more attention. Evolutionary computation has also provided a powerful driving force for the optimization and improvement of deep learning models. In this paper, we propose an image object detection method based on self-supervised and data-driven learning. Differ from other methods, our approach stands out due to its innovative use of multispectral data fusion and evolutionary computation for model optimization. Specifically, our method uniquely combines visible light images and infrared images to detect and identify image targets. Firstly, we utilize a self-supervised learning method and the AutoEncoder model to perform high-dimensional feature extraction on the two types of images. Secondly, we fuse the extracted features from the visible light and infrared images to detect and identify objects. Thirdly, we introduce a model parameter optimization method using evolutionary learning algorithms to enhance model performance. Validation on public datasets shows that our method achieves comparable or superior performance to existing methods. The image object recognition and detection technology are widely used in many scenarios. In recent years, big data has become increasingly abundant, and big data-driven artificial intelligence models have attracted more and more attention. Evolutionary computation has also provided a powerful driving force for the optimization and improvement of deep learning models. In this paper, we propose an image object detection method based on self-supervised and data-driven learning. Differ from other methods, our approach stands out due to its innovative use of multispectral data fusion and evolutionary computation for model optimization. Specifically, our method uniquely combines visible light images and infrared images to detect and identify image targets. Firstly, we utilize a self-supervised learning method and the AutoEncoder model to perform high-dimensional feature extraction on the two types of images. Secondly, we fuse the extracted features from the visible light and infrared images to detect and identify objects. Thirdly, we introduce a model parameter optimization method using evolutionary learning algorithms to enhance model performance. Validation on public datasets shows that our method achieves comparable or superior performance to existing methods.
ArticleNumber	130
Author	Shen, Xiaoyang Viriyasitavat, Wattana Chamola, Vinay Shankar, Achyut Li, Haibin
Author_xml	– sequence: 1 givenname: Xiaoyang surname: Shen fullname: Shen, Xiaoyang organization: College of Electrical Engineering, Yanshan University, Key Laboratory of Industrial Computer Control Engineering of Hebei Province – sequence: 2 givenname: Haibin surname: Li fullname: Li, Haibin email: hbli_ysu@163.com organization: College of Electrical Engineering, Yanshan University, Key Laboratory of Industrial Computer Control Engineering of Hebei Province – sequence: 3 givenname: Achyut surname: Shankar fullname: Shankar, Achyut organization: WMG, University of Warwick, Department of Cyber Systems Engineering, WMG, University Centre for Research & Development, Chandigarh University, School of Computer Science Engineering, Lovely Professional University, Department of Computer Science and Engineering, Graphic Era Deemed to be University, Center of Research Impact and Outcome, Chitkara University – sequence: 4 givenname: Wattana surname: Viriyasitavat fullname: Viriyasitavat, Wattana organization: Chulalongkorn Business School, Faculty of Commerce and Accountancy, Chulalongkorn University – sequence: 5 givenname: Vinay surname: Chamola fullname: Chamola, Vinay organization: BITS-Pilani
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Cites_doi	10.1109/TSP.2006.879267 10.1109/TPAMI.2012.120 10.1007/s11263-013-0636-x 10.1109/LSP.2017.2789325 10.1109/JSEN.2019.2936916 10.1023/B:VISI.0000022288.19776.77 10.1109/TPAMI.2009.96 10.1016/j.ress.2007.02.009 10.3390/rs13132538 10.1162/neco_a_00990 10.1007/s44196-023-00302-w 10.1145/3072959.3073659 10.1109/MSP.2013.2278992 10.1007/978-3-642-35289-8_30 10.1109/TPAMI.2023.3261282 10.22146/ijccs.54050 10.1007/s11263-006-7934-5 10.1109/CVPR.2008.4587597 10.1109/WACV.2018.00092 10.1109/CVPR.2016.278 10.1109/CVPR.2019.01243 10.1109/CVPR42600.2020.00674 10.1109/CVPR52729.2023.01341 10.1109/CVPR.2018.00973 10.1109/SSCI.2017.8285338 10.1109/CVPR.2019.01061 10.52098/airdj.20217 10.1007/978-3-319-24574-4_28 10.1088/1742-6596/1004/1/012029 10.1016/j.ress.2007.03.027 10.1109/CVPR.2017.19 10.1109/CVPR.2009.5206848 10.1109/ICCV.2019.00156 10.1145/3123266.3123289 10.1609/aaai.v33i01.33018569 10.1109/ICCV.2019.00822 10.1109/CVPR.2019.00834 10.1109/CVPR.2015.7298965 10.1109/ICCV.2017.628 10.1109/CVPR.2019.00265 10.1109/CVPR.2005.177 10.1109/CISES58720.2023.10183503 10.1109/CVPR.2008.4587471 10.1007/978-3-030-01240-3_45 10.1007/978-3-030-01264-9_9
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References	Li, Liang, Shen (CR28) 2017; 20 Tavakkoli-Moghaddam, Safari, Sassani (CR46) 2008; 93 Zhang, Demiris (CR10) 2023; 45 Boykov, Funka-Lea (CR31) 2006; 70 Yang, Yang, Su (CR29) 2018; 44 Xiang, Lv, Yu (CR43) 2019; 19 CR39 CR38 CR37 CR36 CR35 CR32 Levinshtein, Stere, Kutulakos (CR33) 2009; 31 Bekkerman, Tabrikian (CR1) 2006; 54 CR2 Putra, A I A, Utaminingrum, Mahmudy (CR25) 2020; 14 CR4 CR3 Sirisha, Praveen, Srinivasu (CR52) 2023; 16 CR5 Li, Wong, Lo (CR27) 2018; 25 CR7 CR9 CR49 CR48 CR47 CR45 Felzenszwalb, Huttenlocher (CR30) 2004; 59 CR44 CR42 CR41 Sánchez, Perronnin, Mensink (CR15) 2013; 105 Rawat, Wang (CR8) 2017; 29 Achanta, Shaji, Smith (CR34) 2012; 34 Xiao, Wang, Miao (CR40) 2021; 13 CR19 CR18 CR17 CR14 CR13 CR11 CR53 CR51 CR50 Coates, Ng (CR16) 2012 Nasrabadi (CR6) 2013; 31 CR26 CR24 CR23 CR22 CR21 CR20 Iizuka, Simo-Serra, Ishikawa (CR12) 2017; 36 Y Boykov (988_CR31) 2006; 70 988_CR26 S Iizuka (988_CR12) 2017; 36 988_CR20 988_CR22 988_CR21 988_CR24 988_CR23 X Zhang (988_CR10) 2023; 45 A Levinshtein (988_CR33) 2009; 31 J Sánchez (988_CR15) 2013; 105 X Xiang (988_CR43) 2019; 19 988_CR14 988_CR17 988_CR19 988_CR18 F Putra (988_CR25) 2020; 14 988_CR51 988_CR50 988_CR53 988_CR11 988_CR13 W Rawat (988_CR8) 2017; 29 988_CR4 988_CR3 R Tavakkoli-Moghaddam (988_CR46) 2008; 93 988_CR2 988_CR48 988_CR47 988_CR49 988_CR42 988_CR41 GC Yang (988_CR29) 2018; 44 988_CR44 988_CR45 R Achanta (988_CR34) 2012; 34 U Sirisha (988_CR52) 2023; 16 J Li (988_CR28) 2017; 20 I Bekkerman (988_CR1) 2006; 54 NM Nasrabadi (988_CR6) 2013; 31 988_CR37 988_CR7 988_CR36 988_CR39 988_CR5 A Coates (988_CR16) 2012 988_CR38 988_CR9 X Xiao (988_CR40) 2021; 13 PF Felzenszwalb (988_CR30) 2004; 59 988_CR32 988_CR35 J Li (988_CR27) 2018; 25
References_xml	– volume: 54 start-page: 3873 issue: 10 year: 2006 end-page: 83 ident: CR1 article-title: Target detection and localization using MIMO radars and sonars[J] publication-title: IEEE Trans Signal Process doi: 10.1109/TSP.2006.879267 – ident: CR45 – ident: CR22 – volume: 34 start-page: 2274 issue: 11 year: 2012 end-page: 82 ident: CR34 article-title: SLIC superpixels compared to state-of-the-art superpixel methods[J] publication-title: IEEE Trans Pattern Anal Mach Intell doi: 10.1109/TPAMI.2012.120 – volume: 105 start-page: 222 issue: 3 year: 2013 end-page: 45 ident: CR15 article-title: Image classification with the fisher vector: theory and practice[J] publication-title: Int J Comput Vision doi: 10.1007/s11263-013-0636-x – ident: CR49 – ident: CR4 – ident: CR39 – ident: CR51 – volume: 25 start-page: 288 issue: 2 year: 2018 end-page: 92 ident: CR27 article-title: Multiple object detection by a deformable part-based model and an R-CNN[J] publication-title: IEEE Signal Process Lett doi: 10.1109/LSP.2017.2789325 – volume: 19 start-page: 11706 issue: 23 year: 2019 end-page: 13 ident: CR43 article-title: Cross-modality person re-identification based on dual-path multi-branch network[J] publication-title: IEEE Sens J doi: 10.1109/JSEN.2019.2936916 – ident: CR35 – ident: CR42 – ident: CR21 – ident: CR19 – volume: 59 start-page: 167 year: 2004 end-page: 81 ident: CR30 article-title: Efficient graph-based image segmentation[J] publication-title: Int J Comput Vision doi: 10.1023/B:VISI.0000022288.19776.77 – ident: CR50 – ident: CR11 – ident: CR9 – ident: CR32 – ident: CR36 – ident: CR5 – volume: 31 start-page: 2290 issue: 12 year: 2009 end-page: 7 ident: CR33 article-title: Turbopixels: fast superpixels using geometric flows[J] publication-title: IEEE Trans Pattern Anal Mach Intell doi: 10.1109/TPAMI.2009.96 – ident: CR26 – ident: CR18 – volume: 93 start-page: 550 issue: 4 year: 2008 end-page: 6 ident: CR46 article-title: Reliability optimization of series-parallel systems with a choice of redundancy strategies using a genetic algorithm[J] publication-title: Reliab Eng Syst Saf doi: 10.1016/j.ress.2007.02.009 – ident: CR47 – ident: CR14 – ident: CR2 – ident: CR37 – ident: CR53 – volume: 13 start-page: 2538 issue: 13 year: 2021 ident: CR40 article-title: Infrared and visible image object detection via focused feature enhancement and cascaded semantic extension[J] publication-title: Remote Sens doi: 10.3390/rs13132538 – volume: 29 start-page: 2352 issue: 9 year: 2017 end-page: 449 ident: CR8 article-title: Deep convolutional neural networks for image classification: a comprehensive review[J] publication-title: Neural Comput doi: 10.1162/neco_a_00990 – volume: 16 start-page: 126 issue: 1 year: 2023 ident: CR52 article-title: Statistical analysis of design aspects of various YOLO-based deep learning models for object detection[J] publication-title: Int J Comput Intell Syst doi: 10.1007/s44196-023-00302-w – ident: CR23 – volume: 36 start-page: 1 issue: 4 year: 2017 end-page: 14 ident: CR12 article-title: Globally and locally consistent image completion[J] publication-title: ACM Trans Graphics (ToG) doi: 10.1145/3072959.3073659 – ident: CR44 – volume: 44 start-page: 2238 issue: 12 year: 2018 end-page: 49 ident: CR29 article-title: Improved YOLO feature extraction algorithm and its application to privacy situation detection of social robots[J] publication-title: Acta Automatica Sinica – ident: CR48 – ident: CR3 – ident: CR38 – volume: 31 start-page: 34 issue: 1 year: 2013 end-page: 44 ident: CR6 article-title: Hyperspectral target detection: an overview of current and future challenges[J] publication-title: IEEE Signal Process Mag doi: 10.1109/MSP.2013.2278992 – ident: CR17 – ident: CR13 – start-page: 561 year: 2012 end-page: 80 ident: CR16 publication-title: Learning feature representations with k-means[M]//Neural networks: tricks of the trade doi: 10.1007/978-3-642-35289-8_30 – volume: 20 start-page: 985 issue: 4 year: 2017 end-page: 96 ident: CR28 article-title: Scale-aware fast R-CNN for pedestrian detection[J] publication-title: IEEE Trans Multimedia – ident: CR7 – ident: CR41 – volume: 45 start-page: 10535 issue: 8 year: 2023 end-page: 54 ident: CR10 article-title: Visible and infrared image fusion using deep learning[J] publication-title: IEEE Trans Pattern Anal Mach Intell doi: 10.1109/TPAMI.2023.3261282 – volume: 14 start-page: 231 issue: 3 year: 2020 end-page: 42 ident: CR25 article-title: HOG feature extraction and KNN classification for detecting vehicle in the highway[J] publication-title: IJCCS (Indonesian J Comput Cybernetics Systems) doi: 10.22146/ijccs.54050 – ident: CR24 – ident: CR20 – volume: 70 start-page: 109 issue: 2 year: 2006 end-page: 31 ident: CR31 article-title: Graph cuts and efficient ND image segmentation[J] publication-title: Int J Comput Vision doi: 10.1007/s11263-006-7934-5 – ident: 988_CR42 doi: 10.1109/CVPR.2008.4587597 – ident: 988_CR21 doi: 10.1109/WACV.2018.00092 – volume: 93 start-page: 550 issue: 4 year: 2008 ident: 988_CR46 publication-title: Reliab Eng Syst Saf doi: 10.1016/j.ress.2007.02.009 – volume: 70 start-page: 109 issue: 2 year: 2006 ident: 988_CR31 publication-title: Int J Comput Vision doi: 10.1007/s11263-006-7934-5 – volume: 13 start-page: 2538 issue: 13 year: 2021 ident: 988_CR40 publication-title: Remote Sens doi: 10.3390/rs13132538 – ident: 988_CR11 doi: 10.1109/CVPR.2016.278 – ident: 988_CR18 – ident: 988_CR39 doi: 10.1109/CVPR.2019.01243 – volume: 105 start-page: 222 issue: 3 year: 2013 ident: 988_CR15 publication-title: Int J Comput Vision doi: 10.1007/s11263-013-0636-x – ident: 988_CR7 doi: 10.1109/CVPR42600.2020.00674 – ident: 988_CR9 doi: 10.1109/CVPR52729.2023.01341 – ident: 988_CR50 – ident: 988_CR22 doi: 10.1109/CVPR.2018.00973 – volume: 14 start-page: 231 issue: 3 year: 2020 ident: 988_CR25 publication-title: IJCCS (Indonesian J Comput Cybernetics Systems) doi: 10.22146/ijccs.54050 – ident: 988_CR44 doi: 10.1109/SSCI.2017.8285338 – ident: 988_CR23 doi: 10.1109/CVPR.2019.01061 – ident: 988_CR26 doi: 10.52098/airdj.20217 – ident: 988_CR36 doi: 10.1007/978-3-319-24574-4_28 – volume: 20 start-page: 985 issue: 4 year: 2017 ident: 988_CR28 publication-title: IEEE Trans Multimedia – volume: 19 start-page: 11706 issue: 23 year: 2019 ident: 988_CR43 publication-title: IEEE Sens J doi: 10.1109/JSEN.2019.2936916 – ident: 988_CR48 doi: 10.1088/1742-6596/1004/1/012029 – ident: 988_CR45 doi: 10.1016/j.ress.2007.03.027 – ident: 988_CR13 doi: 10.1109/CVPR.2017.19 – volume: 16 start-page: 126 issue: 1 year: 2023 ident: 988_CR52 publication-title: Int J Comput Intell Syst doi: 10.1007/s44196-023-00302-w – volume: 54 start-page: 3873 issue: 10 year: 2006 ident: 988_CR1 publication-title: IEEE Trans Signal Process doi: 10.1109/TSP.2006.879267 – volume: 29 start-page: 2352 issue: 9 year: 2017 ident: 988_CR8 publication-title: Neural Comput doi: 10.1162/neco_a_00990 – ident: 988_CR4 doi: 10.1109/CVPR.2009.5206848 – volume: 59 start-page: 167 year: 2004 ident: 988_CR30 publication-title: Int J Comput Vision doi: 10.1023/B:VISI.0000022288.19776.77 – ident: 988_CR51 – ident: 988_CR38 doi: 10.1109/ICCV.2019.00156 – volume: 31 start-page: 2290 issue: 12 year: 2009 ident: 988_CR33 publication-title: IEEE Trans Pattern Anal Mach Intell doi: 10.1109/TPAMI.2009.96 – ident: 988_CR41 – volume: 44 start-page: 2238 issue: 12 year: 2018 ident: 988_CR29 publication-title: Acta Automatica Sinica – volume: 34 start-page: 2274 issue: 11 year: 2012 ident: 988_CR34 publication-title: IEEE Trans Pattern Anal Mach Intell doi: 10.1109/TPAMI.2012.120 – ident: 988_CR5 – ident: 988_CR47 doi: 10.1145/3123266.3123289 – ident: 988_CR49 doi: 10.1609/aaai.v33i01.33018569 – ident: 988_CR37 doi: 10.1109/ICCV.2019.00822 – volume: 45 start-page: 10535 issue: 8 year: 2023 ident: 988_CR10 publication-title: IEEE Trans Pattern Anal Mach Intell doi: 10.1109/TPAMI.2023.3261282 – ident: 988_CR3 doi: 10.1109/CVPR.2019.00834 – ident: 988_CR35 doi: 10.1109/CVPR.2015.7298965 – start-page: 561 volume-title: Learning feature representations with k-means[M]//Neural networks: tricks of the trade year: 2012 ident: 988_CR16 doi: 10.1007/978-3-642-35289-8_30 – ident: 988_CR20 doi: 10.1109/ICCV.2017.628 – ident: 988_CR24 doi: 10.1109/CVPR.2019.00265 – volume: 25 start-page: 288 issue: 2 year: 2018 ident: 988_CR27 publication-title: IEEE Signal Process Lett doi: 10.1109/LSP.2017.2789325 – ident: 988_CR14 doi: 10.1109/CVPR.2005.177 – ident: 988_CR53 doi: 10.1109/CISES58720.2023.10183503 – ident: 988_CR32 doi: 10.1109/CVPR.2008.4587471 – volume: 31 start-page: 34 issue: 1 year: 2013 ident: 988_CR6 publication-title: IEEE Signal Process Mag doi: 10.1109/MSP.2013.2278992 – ident: 988_CR2 doi: 10.1007/978-3-030-01240-3_45 – ident: 988_CR19 – volume: 36 start-page: 1 issue: 4 year: 2017 ident: 988_CR12 publication-title: ACM Trans Graphics (ToG) doi: 10.1145/3072959.3073659 – ident: 988_CR17 doi: 10.1007/978-3-030-01264-9_9
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Snippet	The image object recognition and detection technology are widely used in many scenarios. In recent years, big data has become increasingly abundant, and big... Abstract The image object recognition and detection technology are widely used in many scenarios. In recent years, big data has become increasingly abundant,...
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SubjectTerms	Artificial intelligence Big Data Communications Engineering Computation Computational Science and Engineering Computer Science Data integration Data Mining and Knowledge Discovery Data processing Database Management Deep learning Evolutionary algorithms Evolutionary computation Extraction Feature extraction Feature recognition Image enhancement Image processing Imagery Information Storage and Retrieval Infrared imagery Learning Machine learning Mathematical Applications in Computer Science Networks Object detection Object recognition Optimization Parameter identification Self-supervised learning Target detection
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Title	Evolutionary computation-based self-supervised learning for image processing: a big data-driven approach to feature extraction and fusion for multispectral object detection
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