[1] [1] WANG Can, BU Leping. Overview of target detection algorithms based on convolutional neural networks[J]. Naval Electronic Engineering, 2021, 41(9): 161-169.

[2] [2] HAO Yongping, CAO Zhaorui, BAI Fan, et al Research on infrared visible image fusion and target recognition algorithm based on region of interest mask convolution neural network[J]. Acta PHOTONICA Sinica, 2021, 50 (2): 84-98.

[3] [3] LIU Qi, WANG Maojun, GAO Qiang, et al Electrical equipment fault detection based on infrared imaging technology[J]. Electric Measurement and Instrumentation, 2019, 56(10): 122-126.

[4] [4] XIA J, LU Y, TAN L, et al. Intelligent fusion of infrared and visible image data based on convolutional sparse representation and improved pulsecoupled neural network[J]. Computers, Materials and Continua, 2021, 67(1): 613-624.

[5] [5] WANG Yong, ZHANG Ying, LIAO Ruchao, et al. UAV image fusion method based on visible light, thermal infrared and lidar sensing[J]. Laser Journal, 2020, 41(2): 141-145.

[6] [6] ZHANG S, LI X, ZHANG X, et al. Infrared and visible image fusion based on saliency detection and two-scale transform decomposition[J]. Infrared Physics & Technology, 2021, 114(3): 103626.

[7] [7] WANG Chuanyang. Research on Power Equipment Recognition Based on Infrared and Visible Images[D]. Beijing: North China Electric Power University, 2017.

[8] [8] LI H, WU X J. Infrared and visible image fusion using Latent low-rank representation[J]. Arxiv Preprint Arxiv, 2018: 1804.08992.

[9] [9] HUI L, WU X J. DenseFuse: A fusion approach to infrared and visible images[J]. IEEE Transactions on Image Processing, 2018, 28(5): 2614-2623.

[10] [10] TANG Cong, LING Yongshun, YANG Hua, et al. Decision-level fusion tracking of infrared and visible light based on deep learning[J]. Advances in Lasers and Optoelectronics, 2019, 56(7): 209-216.

[11] [11] MA J, TANG L, XU M, et al. STDFusionNet: an infrared and visible image fusion network based on salient object detection[J]. IEEE Transactions on Instrumentation and Measurement, 2021, 70: 1-13.

[12] [12] YANG Xuehe, LIU Huanxi, XIAO Jianli. A review of multimodal biometric feature extraction and correlation evaluation[J]. Chinese Journal of Image and Graphics, 2020, 25(8): 1529-1538.

[13] [13] WANG Z, XIN Z, HUANG X, et al. Overview of SAR image feature extraction and object recognition[J]. Springer, 2021, 234(4): 69-75.

[14] [14] WEI Z. A summary of research and application of deep learning[J]. International Core Journal of Engineering, 2019, 5(9): 167-169.

[15] [15] Bochkovskiy A, WANG C Y, LIAO H. YOLOv4: Optimal speed and accuracy of object detection[J]. Arxiv Preprint Arxiv, 2020: 2004.10934.

[16] [16] HE K, ZHANG X, REN S, et al. Deep residual learning for image recognition[C]// IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016: 770-778.

[17] [17] Howard A, Sandler M, Chen B, et al. Searching for MobileNetV3 [C]//IEEE International Conference on Computer Vision (ICCV), 2020: 1314-1324.

[18] [18] CHEN H, WANG Y, XU C, et al. AdderNet: Do we really need multiplications in deep learning?[C]// 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, 2020: 1465-1474.

[19] [19] SONG Penghan, XIN Huaisheng, LIU Nannan. Multi-source feature fusion recognition of marine ship targets based on deep learning[J]. Journal of the Chinese Academy of Electronic Sciences, 2021, 16(2): 127-133.

[20] [20] Hassan E. Multiple object tracking using feature fusion in hierarchical LSTMs[J]. The Journal of Engineering, 2020(10): 893-899.

[21] [21] LIN T Y, Dollar P, Girshick R, et al. Feature pyramid networks for object detection[C]// IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017: 936-944.

[22] [22] LIU S, HUANG D, WANG Y. Learning spatial fusion for single-shot object detection[J]. Arxiv Preprint Arxiv, 2019: 1911.09516v1.

[23] [23] LI C, ZHAO N, LU Y, et al. Weighted sparse representation regularized graph learning for RGB-T object tracking[C]// Acm on Multimedia Conference, ACM, 2017: 1856-1864.

[24] [24] XIAO X, WANG B, MIAO L, et al. Infrared and visible image object detection via focused feature enhancement and cascaded semantic extension[J]. Remote Sensing, 2021, 13(13): 2538.