Electronics Optics & Control, Volume. 29, Issue 7, 96(2022)
A Pedestrian Detection Method Based on YOLOv5s and Image Fusion
[1] [1] DALAL N, TRIGGS B.Histograms of oriented gradients for human detection[C]//IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).San Diego:IEEE, 2005:886-893.
[2] [2] CORTES C, VAPNIK V.Support-vector networks[J].Machine Learning, 1995, 20(3):273-297.
[3] [3] FELZENSZWALB P F, GIRSHICK R B, MCALLESTER D, et al.Object detection with discriminatively trained part-based models[J].IEEE Transactions on Pattern Analysis and Machine Intelligence, 2009, 32(9):1627-1645.
[4] [4] GIRSHICK R, DONAHUE J, DARRELL T, et al.Rich feature hierarchies for accurate object detection and semantic segmentation[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition.Columbus:IEEE, 2014:580-587.
[5] [5] GIRSHICK R.Fast R-CNN[C]//Proceedings of the IEEE International Conference on Computer Vision.Santiago:IEEE, 2015:1440-1448.
[6] [6] REN S Q, HE K M, GIRSHICK R, et al.Faster R-CNN:towards real-time object detection with region proposal networks[C]//Proceedings of International Conference on Neural Information Processing Systems.Cambridge:MIT Press, 2015:91-99.
[7] [7] REDMON J, DIVVALA S, GIRSHICK R, et al.You only look once:unified, real-time object detection[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition.Las Vegas:IEEE, 2016:779-788.
[8] [8] HU J, SHEN L, SUN G.Squeeze-and-excitation networks[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition.Salt Lake City:IEEE, 2018:7132-7141.
[9] [9] WANG C Y, LIAO H Y, WU Y H, et al.CSPNet:a new backbone that can enhance learning capability of CNN[C]//Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops.Seattle:IEEE, 2020:390-391.
[10] [10] LIN T Y, DOLLR P, GIRSHICK R, et al.Feature pyramid networks for object detection[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition.Honolulu:IEEE, 2017:2117-2125.
[11] [11] LIU S, QI L, QIN H F, et al.Path aggregation network for instance segmentation[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition.Salt Lake City:IEEE, 2018:8759-8768.
[12] [12] LOWE D G.Distinctive image features from scale-invariant keypoints[J].International Journal of Computer Vision, 2004, 60(2):91-110.
[13] [13] MA J Y, YU W, LIANG P W, et al.FusionGAN:a gener- ative adversarial network for infrared and visible image fusion[J].Information Fusion, 2019, 48:11-26.
[14] [14] RONNEBERGER O, FISCHER P, BROX T.U-net:con-volutional networks for biomedical image segmentation[C]//International Conference on Medical Image Computing and Computer-Assisted Intervention.Cham: Springer, 2015:234-241.
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CHEN Shiquan, WANG Congqing, ZHOU Yongjun. A Pedestrian Detection Method Based on YOLOv5s and Image Fusion[J]. Electronics Optics & Control, 2022, 29(7): 96
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Received: Jun. 26, 2021
Accepted: --
Published Online: Aug. 1, 2022
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