Infrared and Laser Engineering, Volume. 51, Issue 12, 20220253(2022)

Lightweight infrared dim vehicle target detection algorithm based on deep learning

Renhao Cai1, Ning Cheng1, Zhiyong Peng1, Shize Dong1, Jianmin An2, and Gang Jin3
Author Affiliations
  • 1Tianjin Jinhang Institute of Technical Physics, Tianjin 300308, China
  • 2The Third Military Representative Office in Tianjin, Tianjin 300308, China
  • 3Tianjin University, Tianjin 300072, China
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    References(14)

    [1] Li Xudong, Ye Mao, Li Tao. A review of object detection research based on convolutional neural network[J]. Computer Application Research, 34, 2881-2887(2017).

    [2] Tang Cong, Ling Yongshun, Yang Hua, et al. Visual tracking method for object detection based on deep learning[J]. Infrared and Laser Engineering, 47, 0526001(2018).

    [3] Krizhevsky A, Sutskever I, Hinton G. Imagenet classification with deep convolutional neural networks[J]. Advances in Neural Information Processing Systems, 25, 1097-1105(2012).

    [4] [4] Szegedy C, Liu W, Jia Y, et al. Going deeper with convolutions[C]Proceedings of the IEEE Conference on Computer Vision Pattern Recognition, 2015: 19.

    [5] [5] Simonyan K, Zisserman A. Very deep convolutional wks f largescale image recognition[EBOL]. (20140904)[20220320]. https:arxiv.gabs1409.1556v4.

    [6] [6] He K M, Zhang X Y, Ren S Q, et al. Deep residual learning f image recognition [C]Proceedings of the IEEE Conference on Computer Vision Pattern Recognition , 2016: 770778.

    [7] Zhou Xiaoyan, Wang Ke, Li Lingyan. A review of target detection algorithms based on deep learning[J]. Electronic Measurement Technology, 40, 89-94(2017).

    [8] [8] Girshick R, Donahue J, Darrell T, et al. Rich feature hierarchies f accurate object detection semantic segmentation[C]Proceedings of the IEEE Conference on Computer Vision Pattern Recognition, 2014: 580587.

    [9] [9] Redmon J , Divvala S , Girshick R , et al. You only look once: Unified, RealTimeObject detection[C]Proceedings of the IEEE Conference on Computer Vision Pattern Recognition 2016: 779788.

    [10] Ren H, Wang X G. Review of attention mechanism[J]. Journal of Computer Applications, 41, 1-6(2021).

    [11] Hu J, Shen L, Albanie S, et al. Squeeze-and-excitation networks[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 42, 2011-2023(2020).

    [12] [12] Wang Q, Wu B, Zhu P, et al. ECA: Efficient channel attention f deep convolutional neural wks[C]Proceedings of the IEEE Conference on Computer Vision Pattern Recognition, 2020: 1153111539.

    [13] [13] Qin X, Wang Z, Bai Y, et al. FFA: Feature fusion attention wk f single image dehazing[C]Proceedings of the National Conference on Artificial Intelligence in Association f the Advancement of Artificial Intelligence, 2020: 19.

    [14] [14] Zhang Y, Tian Y, Kong Y, et al. Residual dense wk f image superresolution[C]Proceedings of the IEEE Conference on Computer Vision Pattern Recognition, 2018: 24722481.

    CLP Journals

    [1] Genghuan LIU, Xiangjin ZENG, Jiazhen DOU, Zhenbo REN, Liyun ZHONG, Jianglei DI, Yuwen QIN. Review of advances in small object detection technology based on deep learning (invited)[J]. Infrared and Laser Engineering, 2024, 53(9): 20240253

    [2] Yinhui Zhang, Kai Ji, Zifen He, Guangchen Chen. Attention-guided multi-scale infrared real-time detection of pedestrian and vehicle[J]. Infrared and Laser Engineering, 2024, 53(5): 20240063

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    Renhao Cai, Ning Cheng, Zhiyong Peng, Shize Dong, Jianmin An, Gang Jin. Lightweight infrared dim vehicle target detection algorithm based on deep learning[J]. Infrared and Laser Engineering, 2022, 51(12): 20220253

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    Paper Information

    Category: Image processing

    Received: Mar. 20, 2022

    Accepted: --

    Published Online: Jan. 10, 2023

    The Author Email:

    DOI:10.3788/IRLA20220253

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