[1] Girshick R, Donahue J, Darrell T et al. Rich feature hierarchies for accurate object detection and semantic segmentation[C], 580-587(2014).
[2] Girshick R. Fast R-CNN[C], 1440-1448(2015).
[3] Ren S Q, He K M, Girshick R et al. Faster R-CNN: towards real-time object detection with region proposal networks[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 39, 1137-1149(2017).
[4] Redmon J, Divvala S, Girshick R et al. You only look once: unified, real-time object detection[C], 779-788(2016).
[5] Liu W, Anguelov D, Erhan D et al. SSD: single shot MultiBox detector[M]. Leibe B, Matas J, Sebe N, et al. Computer vision-ECCV 2016, 9905, 21-37(2016).
[6] Xiao Y X, Jiang A W, Ye J H et al. Making of night vision: object detection under low-illumination[J]. IEEE Access, 8, 123075-123086(2020).
[8] Wang K, Liu M Z. Object recognition at night scene based on DCGAN and faster R-CNN[J]. IEEE Access, 8, 193168-193182(2020).
[9] Tao Q Y, Ren K, Feng B et al. An accurate low-light object detection method based on pyramid networks[J]. Proceedings of SPIE, 11550, 1155015(2020).
[12] Ma Y K, Liu H, Ling C X et al. Research on mangrove single wood object detection based on improved YOLOv5[J]. Laser & Optoelectronics Progress, 59, 1828003(2022).
[13] Guo X J, Li Y, Ling H B. LIME: low-light image enhancement via illumination map estimation[J]. IEEE Transactions on Image Processing, 26, 982-993(2017).
[14] Jiang Y F, Gong X Y, Liu D et al. EnlightenGAN: deep light enhancement without paired supervision[J]. IEEE Transactions on Image Processing, 30, 2340-2349(2021).
[15] Guo C L, Li C Y, Guo J C et al. Zero-reference deep curve estimation for low-light image enhancement[C], 1777-1786(2020).
[16] Loh Y P, Chan C S. Getting to know low-light images with the Exclusively Dark dataset[J]. Computer Vision and Image Understanding, 178, 30-42(2019).
[17] Li X, Wang W H, Hu X L et al. Selective kernel networks[C], 510-519(2019).
[18] Wang X L, Girshick R, Gupta A et al. Non-local neural networks[C], 7794-7803(2018).
[19] Everingham M, Gool L, Williams C K I et al. The pascal visual object classes (VOC) challenge[J]. International Journal of Computer Vision, 88, 303-338(2010).