[1] ZHANG J Y, ZHANG R F, LIU Y H et al. Multimodal image semantic segmentation based on attention mechanism[J]. Chinese Journal of Liquid Crystals and Displays, 38, 975-984(2023).

[2] ZHANG Y, GUO J L, WANG F et al. Image rain removal algorithm based on multi-cascade progressive convolution structure[J]. Chinese Journal of Liquid Crystals and Displays, 38, 1409-1422(2023).

[3] CHEN L, AI H Z, ZHUANG Z J et al. Real-time multiple people tracking with deeply learned candidate selection and person Re-identification[C], 1-6(2018).

[4] DONG J Y, ZHANG L Y, ZHANG H W et al. Occlusion-aware GAN for face de-occlusion in the wild[C], 1-6(2020).

[5] ZUO C, QIAN J M, FENG S J et al. Deep learning in optical metrology: a review[J]. Light: Science & Applications, 11, 39(2022).

[6] SITU G. Deep holography[J]. Light: Advanced Manufacturing, 3, 278-300(2022).

[7] LUO Y, ZHAO Y F, LI J X et al. Computational imaging without a computer: seeing through random diffusers at the speed of light[J]. eLight, 2, 4(2022).

[8] LECUN Y, BOTTOU L, BENGIO Y et al. Gradient-based learning applied to document recognition[J]. Proceedings of the IEEE, 86, 2278-2324(1998).

[9] SHELHAMER E, LONG J, DARRELL T. Fully convolutional networks for semantic segmentation[C], 3431-3440(2015).

[10] KRIZHEVSKY A, SUTSKEVER I, HINTON G E. ImageNet classification with deep convolutional neural networks[C], 1097-1105(2012).

[11] YANG Z T, SUN Y N, SHU L et al. 3DSSD: Point-based 3D single stage object detector[C], 11037-11045(2020).

[12] GIRSHICK R, DONAHUE J, DARRELL T et al. Rich feature hierarchies for accurate object detection and semantic segmentation[C], 580-587(2014).

[13] HEARST M A, DUMAIS S T, OSUNA E et al. Support vector machines[J]. IEEE Intelligent Systems and their applications, 13, 18-28(1998).

[14] GIRSHICK R. Fast R-CNN[C], 1440-1448(2015).

[15] 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).

[16] REDMON J, DIVVALA S, GIRSHICK R et al. You only look once: Unified, real-time object detection[C], 779-788(2016).

[17] REDMON J, FARHADI A. YOLO9000: better, faster, stronger[C], 65117-6525(2017).

[18] REDMON J, FARHADI A. YOLOv3: An incremental improvement[J/OL]. arXiv(2018).

[19] BOCHKOVSKIY A, WANG C Y, LIAO H Y M. YOLOv4: Optimal speed and accuracy of object detection[J/OL]. arXiv(2020).

[20] GE Z, LIU S T, WANG F et al. YOLOX: Exceeding YOLO series in 2021[J/OL]. arXiv(2021).

[21] YU J H, JIANG Y N, WANG Z Y et al. UnitBox: An advanced object detection network[C], 516-520(2016).

[22] REZATOFIGHI H, TSOI N, GWAK J et al. Generalized intersection over union: A metric and a loss for bounding box regression[C], 658-666(2019).

[23] ZHENG Z H, WANG P, LIU W et al. Distance-IoU loss: Faster and better learning for bounding box regression[C], 12993-13000(2020).

[24] SERMANET P, EIGEN D, ZHANG X et al. Overfeat: Integrated recognition, localization and detection using convolutional networks[C](2014).

[25] LIU W, ANGUELOV D, ERHAN D et al. SSD: Single shot multiBox detector[C], 21-37(2016).

[26] LIN T Y, GOYAL P, GIRSHICK R et al. Focal loss for dense object detection[C], 2999-3007(2017).

[27] TAN M X, CHEN B, PANG R M et al. MnasNet: Platform-aware neural architecture search for mobile[C], 2815-2823(2019).