{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,11,19]],"date-time":"2024-11-19T18:31:04Z","timestamp":1732041064800},"reference-count":44,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2022,3,1]],"date-time":"2022-03-01T00:00:00Z","timestamp":1646092800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2022,3,1]],"date-time":"2022-03-01T00:00:00Z","timestamp":1646092800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2022,3,1]],"date-time":"2022-03-01T00:00:00Z","timestamp":1646092800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2022,3,1]],"date-time":"2022-03-01T00:00:00Z","timestamp":1646092800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2022,3,1]],"date-time":"2022-03-01T00:00:00Z","timestamp":1646092800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2022,3,1]],"date-time":"2022-03-01T00:00:00Z","timestamp":1646092800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61827901","61936011","62088101","62171038"],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Knowledge-Based Systems"],"published-print":{"date-parts":[[2022,3]]},"DOI":"10.1016\/j.knosys.2021.108010","type":"journal-article","created":{"date-parts":[[2021,12,23]],"date-time":"2021-12-23T16:22:37Z","timestamp":1640276557000},"page":"108010","update-policy":"http:\/\/dx.doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":57,"special_numbering":"C","title":["LE-GAN: Unsupervised low-light image enhancement network using attention module and identity invariant loss"],"prefix":"10.1016","volume":"240","author":[{"ORCID":"http:\/\/orcid.org\/0000-0003-0221-4750","authenticated-orcid":false,"given":"Ying","family":"Fu","sequence":"first","affiliation":[]},{"given":"Yang","family":"Hong","sequence":"additional","affiliation":[]},{"given":"Linwei","family":"Chen","sequence":"additional","affiliation":[]},{"given":"Shaodi","family":"You","sequence":"additional","affiliation":[]}],"member":"78","reference":[{"issue":"6","key":"10.1016\/j.knosys.2021.108010_b1","doi-asserted-by":"crossref","first-page":"1137","DOI":"10.1109\/TPAMI.2016.2577031","article-title":"Faster r-cnn: towards real-time object detection with region proposal networks","volume":"39","author":"Ren","year":"2016","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"10.1016\/j.knosys.2021.108010_b2","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2020.105590","article-title":"Object detection binary classifiers methodology based on deep learning to identify small objects handled similarly: Application in video surveillance","volume":"194","author":"P\u00e9rez-Hern\u00e1ndez","year":"2020","journal-title":"Knowl.-Based Syst."},{"key":"10.1016\/j.knosys.2021.108010_b3","doi-asserted-by":"crossref","first-page":"86","DOI":"10.1016\/j.knosys.2019.02.013","article-title":"Multi-criteria active deep learning for image classification","volume":"172","author":"Yuan","year":"2019","journal-title":"Knowl.-Based Syst."},{"key":"10.1016\/j.knosys.2021.108010_b4","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2021.107033","article-title":"A dual-stream framework guided by adaptive gaussian maps for interactive image segmentation","volume":"223","author":"Ding","year":"2021","journal-title":"Knowl.-Based Syst."},{"issue":"2","key":"10.1016\/j.knosys.2021.108010_b5","doi-asserted-by":"crossref","first-page":"982","DOI":"10.1109\/TIP.2016.2639450","article-title":"Lime: Low-light image enhancement via illumination map estimation","volume":"26","author":"Guo","year":"2016","journal-title":"IEEE Trans. Image Process."},{"issue":"6","key":"10.1016\/j.knosys.2021.108010_b6","doi-asserted-by":"crossref","first-page":"2828","DOI":"10.1109\/TIP.2018.2810539","article-title":"Structure-revealing low-light image enhancement via robust retinex model","volume":"27","author":"Li","year":"2018","journal-title":"IEEE Trans. Image Process."},{"key":"10.1016\/j.knosys.2021.108010_b7","series-title":"2018 13th IEEE International Conference on Automatic Face & Gesture Recognition","first-page":"751","article-title":"Gladnet: Low-light enhancement network with global awareness","author":"Wang","year":"2018"},{"key":"10.1016\/j.knosys.2021.108010_b8","unstructured":"C. Wei, W. Wang, W. Yang, J. Liu, Deep retinex decomposition for low-light enhancement, arXiv preprint arXiv:1808.04560."},{"key":"10.1016\/j.knosys.2021.108010_b9","doi-asserted-by":"crossref","unstructured":"C. Guo, C. Li, J. Guo, C.C. Loy, J. Hou, S. Kwong, R. Cong, Zero-reference deep curve estimation for low-light image enhancement, in: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 2020, pp. 1780\u20131789.","DOI":"10.1109\/CVPR42600.2020.00185"},{"key":"10.1016\/j.knosys.2021.108010_b10","doi-asserted-by":"crossref","first-page":"2340","DOI":"10.1109\/TIP.2021.3051462","article-title":"Enlightengan: Deep light enhancement without paired supervision","volume":"30","author":"Jiang","year":"2021","journal-title":"IEEE Trans. Image Process."},{"key":"10.1016\/j.knosys.2021.108010_b11","doi-asserted-by":"crossref","unstructured":"Y.-S. Chen, Y.-C. Wang, M.-H. Kao, Y.-Y. Chuang, Deep photo enhancer: Unpaired learning for image enhancement from photographs with gans, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2018, pp. 6306\u20136314.","DOI":"10.1109\/CVPR.2018.00660"},{"key":"10.1016\/j.knosys.2021.108010_b12","doi-asserted-by":"crossref","unstructured":"P. Isola, J.-Y. Zhu, T. Zhou, A.A. Efros, Image-to-image translation with conditional adversarial networks, in: Proceedings of the IEEE conference on computer vision and pattern recognition, 2017, pp. 1125\u20131134.","DOI":"10.1109\/CVPR.2017.632"},{"key":"10.1016\/j.knosys.2021.108010_b13","doi-asserted-by":"crossref","first-page":"30","DOI":"10.1016\/j.cviu.2018.10.010","article-title":"Getting to know low-light images with the exclusively dark dataset","volume":"178","author":"Loh","year":"2019","journal-title":"Comput. Vis. Image Underst."},{"key":"10.1016\/j.knosys.2021.108010_b14","series-title":"2017 IEEE Visual Communications and Image Processing","first-page":"1","article-title":"Llcnn: A convolutional neural network for low-light image enhancement","author":"Tao","year":"2017"},{"issue":"2","key":"10.1016\/j.knosys.2021.108010_b15","doi-asserted-by":"crossref","first-page":"593","DOI":"10.1109\/TCE.2007.381734","article-title":"A dynamic histogram equalization for image contrast enhancement","volume":"53","author":"Abdullah-Al-Wadud","year":"2007","journal-title":"IEEE Trans. Consum. Electron."},{"issue":"6","key":"10.1016\/j.knosys.2021.108010_b16","doi-asserted-by":"crossref","first-page":"108","DOI":"10.1038\/scientificamerican1277-108","article-title":"The retinex theory of color vision","volume":"237","author":"Land","year":"1977","journal-title":"Sci. Am."},{"key":"10.1016\/j.knosys.2021.108010_b17","doi-asserted-by":"crossref","unstructured":"Y. Wang, Y. Cao, Z.-J. Zha, J. Zhang, Z. Xiong, W. Zhang, F. Wu, Progressive retinex: Mutually reinforced illumination-noise perception network for low-light image enhancement, in: Proceedings of the 27th ACM International Conference on Multimedia, 2019, pp. 2015\u20132023.","DOI":"10.1145\/3343031.3350983"},{"key":"10.1016\/j.knosys.2021.108010_b18","doi-asserted-by":"crossref","unstructured":"J.-Y. Zhu, T. Park, P. Isola, A.A. Efros, Unpaired image-to-image translation using cycle-consistent adversarial networks, in: Proceedings of the IEEE international conference on computer vision, 2017, pp. 2223\u20132232.","DOI":"10.1109\/ICCV.2017.244"},{"key":"10.1016\/j.knosys.2021.108010_b19","article-title":"Contrast-limited adaptive histogram equalization: speed and effectiveness","volume":"vol. 337","author":"Pizer","year":"1990"},{"issue":"1","key":"10.1016\/j.knosys.2021.108010_b20","doi-asserted-by":"crossref","first-page":"68","DOI":"10.1109\/30.754419","article-title":"Image enhancement based on equal area dualistic sub-image histogram equalization method","volume":"45","author":"Wang","year":"1999","journal-title":"IEEE Trans. Consum. Electron."},{"key":"10.1016\/j.knosys.2021.108010_b21","doi-asserted-by":"crossref","first-page":"147","DOI":"10.1016\/j.neucom.2019.12.093","article-title":"Multi-exposure high dynamic range imaging with informative content enhanced network","volume":"386","author":"Pan","year":"2020","journal-title":"Neurocomputing"},{"key":"10.1016\/j.knosys.2021.108010_b22","doi-asserted-by":"crossref","unstructured":"X. Fu, D. Zeng, Y. Huang, X.-P. Zhang, X. Ding, A weighted variational model for simultaneous reflectance and illumination estimation, in: Proceedings of the IEEE conference on computer vision and pattern recognition, 2016, pp. 2782\u20132790.","DOI":"10.1109\/CVPR.2016.304"},{"issue":"12","key":"10.1016\/j.knosys.2021.108010_b23","doi-asserted-by":"crossref","first-page":"3431","DOI":"10.1109\/TIP.2011.2157513","article-title":"Contextual and variational contrast enhancement","volume":"20","author":"Celik","year":"2011","journal-title":"IEEE Trans. Image Process."},{"issue":"12","key":"10.1016\/j.knosys.2021.108010_b24","doi-asserted-by":"crossref","first-page":"5372","DOI":"10.1109\/TIP.2013.2284059","article-title":"Contrast enhancement based on layered difference representation of 2d histograms","volume":"22","author":"Lee","year":"2013","journal-title":"IEEE Trans. Image Process."},{"issue":"7","key":"10.1016\/j.knosys.2021.108010_b25","doi-asserted-by":"crossref","first-page":"965","DOI":"10.1109\/83.597272","article-title":"A multiscale retinex for bridging the gap between color images and the human observation of scenes","volume":"6","author":"Jobson","year":"1997","journal-title":"IEEE Trans. Image Process."},{"issue":"9","key":"10.1016\/j.knosys.2021.108010_b26","doi-asserted-by":"crossref","first-page":"3538","DOI":"10.1109\/TIP.2013.2261309","article-title":"Naturalness preserved enhancement algorithm for non-uniform illumination images","volume":"22","author":"Wang","year":"2013","journal-title":"IEEE Trans. Image Process."},{"key":"10.1016\/j.knosys.2021.108010_b27","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2020.106235","article-title":"Lightweight image super-resolution with enhanced cnn","volume":"205","author":"Tian","year":"2020","journal-title":"Knowl.-Based Syst."},{"key":"10.1016\/j.knosys.2021.108010_b28","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2021.107013","article-title":"Remote sensing image recovery via enhanced residual learning and dual-luminance scheme","volume":"222","author":"Ren","year":"2021","journal-title":"Knowl.-Based Syst."},{"key":"10.1016\/j.knosys.2021.108010_b29","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2021.107279","article-title":"Eaa-net: A novel edge assisted attention network for single image dehazing","volume":"228","author":"Wang","year":"2021","journal-title":"Knowl.-Based Syst."},{"key":"10.1016\/j.knosys.2021.108010_b30","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2021.106789","article-title":"Efficient texture-aware multi-gan for image inpainting","volume":"217","author":"Hedjazi","year":"2021","journal-title":"Knowl.-Based Syst."},{"key":"10.1016\/j.knosys.2021.108010_b31","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2020.106663","article-title":"Kernel-attended residual network for single image super-resolution","volume":"213","author":"Dun","year":"2021","journal-title":"Knowl.-Based Syst."},{"key":"10.1016\/j.knosys.2021.108010_b32","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2021.106949","article-title":"Designing and training of a dual cnn for image denoising","volume":"226","author":"Tian","year":"2021","journal-title":"Knowl.-Based Syst."},{"key":"10.1016\/j.knosys.2021.108010_b33","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2020.106607","article-title":"Moth swarm algorithm for image contrast enhancement","volume":"212","author":"Luque-Chang","year":"2021","journal-title":"Knowl.-Based Syst."},{"key":"10.1016\/j.knosys.2021.108010_b34","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2020.106617","article-title":"A deep learning based image enhancement approach for autonomous driving at night","volume":"213","author":"Li","year":"2021","journal-title":"Knowl.-Based Syst."},{"issue":"3","key":"10.1016\/j.knosys.2021.108010_b35","doi-asserted-by":"crossref","first-page":"355","DOI":"10.1016\/S0734-189X(87)80186-X","article-title":"Adaptive histogram equalization and its variations","volume":"39","author":"Pizer","year":"1987","journal-title":"Comput. Vis. Graph. Image Process."},{"key":"10.1016\/j.knosys.2021.108010_b36","doi-asserted-by":"crossref","unstructured":"C. Chen, Q. Chen, J. Xu, V. Koltun, Learning to see in the dark, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2018, pp. 3291\u20133300.","DOI":"10.1109\/CVPR.2018.00347"},{"key":"10.1016\/j.knosys.2021.108010_b37","unstructured":"F. Lv, F. Lu, J. Wu, C. Lim, Mbllen: Low-light image\/video enhancement using cnns, in: BMVC, 2018, pp. 220."},{"key":"10.1016\/j.knosys.2021.108010_b38","doi-asserted-by":"crossref","unstructured":"X. Alameda-Pineda, S. Arias, Y. Ban, G. Delorme, L. Girin, R. Horaud, X. Li, B. Morgue, G. Sarrazin, Audio-visual variational fusion for multi-person tracking with robots, in: Proceedings of the 27th ACM International Conference on Multimedia, 2019, pp. 1059\u20131061.","DOI":"10.1145\/3343031.3350590"},{"key":"10.1016\/j.knosys.2021.108010_b39","series-title":"International Conference on Medical Image Computing and Computer-Assisted Intervention","first-page":"234","article-title":"U-net: Convolutional networks for biomedical image segmentation","author":"Ronneberger","year":"2015"},{"key":"10.1016\/j.knosys.2021.108010_b40","series-title":"11th IAPR International Conference on Pattern Recognition. III. Conference C: Image, Speech and Signal Analysis, Vol. 1","first-page":"545","article-title":"Color image enhancement through 3-d histogram equalization","author":"Trahanias","year":"1992"},{"key":"10.1016\/j.knosys.2021.108010_b41","doi-asserted-by":"crossref","unstructured":"J. Si, H. Zhang, C.-G. Li, J. Kuen, X. Kong, A.C. Kot, G. Wang, Dual attention matching network for context-aware feature sequence based person re-identification, in: Proceedings of the IEEE conference on computer vision and pattern recognition, 2018, pp. 5363\u20135372.","DOI":"10.1109\/CVPR.2018.00562"},{"key":"10.1016\/j.knosys.2021.108010_b42","doi-asserted-by":"crossref","unstructured":"T.-Y. Lin, A. RoyChowdhury, S. Maji, Bilinear cnn models for fine-grained visual recognition, in: Proceedings of the IEEE international conference on computer vision, 2015, pp. 1449\u20131457.","DOI":"10.1109\/ICCV.2015.170"},{"key":"10.1016\/j.knosys.2021.108010_b43","unstructured":"H. Jie, S. Li, S. Gang, et al. Squeeze-and-excitation networks, in: Proceedings of the IEEE conference on computer vision and pattern recognition, Vol. 5, 2018."},{"issue":"10","key":"10.1016\/j.knosys.2021.108010_b44","doi-asserted-by":"crossref","first-page":"3037","DOI":"10.1109\/TCSVT.2018.2873599","article-title":"Pedestrian alignment network for large-scale person re-identification","volume":"29","author":"Zheng","year":"2018","journal-title":"IEEE Trans. Circuits Syst. Video Technol."}],"container-title":["Knowledge-Based Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0950705121011151?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0950705121011151?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2023,3,11]],"date-time":"2023-03-11T16:32:13Z","timestamp":1678552333000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0950705121011151"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,3]]},"references-count":44,"alternative-id":["S0950705121011151"],"URL":"https:\/\/doi.org\/10.1016\/j.knosys.2021.108010","relation":{},"ISSN":["0950-7051"],"issn-type":[{"value":"0950-7051","type":"print"}],"subject":[],"published":{"date-parts":[[2022,3]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"LE-GAN: Unsupervised low-light image enhancement network using attention module and identity invariant loss","name":"articletitle","label":"Article Title"},{"value":"Knowledge-Based Systems","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.knosys.2021.108010","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2021 Published by Elsevier B.V.","name":"copyright","label":"Copyright"}],"article-number":"108010"}}
