[1] Zhu D P, Zhan W D, Jiang Y C et al. MIFFuse: a multi-level feature fusion network for infrared and visible images[J]. IEEE Access, 9, 130778-130792(2021).
[2] Zhang T, Zhang L. Multiscale feature fusion-based object detection algorithm[J]. Laser & Optoelectronics Progress, 58, 0215003(2021).
[3] Cheng Y Q, Wang Y, Fan Y Y et al. Lightweight object detection network based on convolutional neural network[J]. Laser & Optoelectronics Progress, 58, 1610023(2021).
[4] Wang Y S, Jia W J, Wang C F et al. Vehicle recognition method based on improved YOLOv3 algorithm[J]. Laser & Optoelectronics Progress, 58, 1610010(2021).
[5] Jiang Y C, Liu Y Q, Zhan W D et al. Lightweight dual-stream residual network for single image super-resolution[J]. IEEE Access, 9, 129890-129901(2021).
[6] Li Y N. A survey of research on deep learning target detection methods[J]. China New Telecommunications, 23, 159-160(2021).
[7] Girshick R, Donahue J, Darrell T et al. Rich feature hierarchies for accurate object detection and semantic segmentation[C], 580-587(2014).
[8] He K M, Zhang X Y, Ren S Q et al. Spatial pyramid pooling in deep convolutional networks for visual recognition[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 37, 1904-1916(2015).
[9] 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).
[10] 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. Lecture notes in computer science, 9905, 21-37(2016).
[11] Redmon J, Divvala S, Girshick R et al. You only look once: unified, real-time object detection[C], 779-788(2016).
[12] Qin P, Tang C M, Liu Y F et al. Infrared target detection method based on improved YOLOv3[J]. Computer Engineering, 48, 211-219(2022).
[13] Ju M, Luo H B, Wang Z B et al. The application of improved YOLO V3 in multi-scale target detection[J]. Applied Sciences, 9, 3775(2019).
[14] Lu L P, Li H S, Ding Z et al. An improved target detection method based on multiscale features fusion[J]. Microwave and Optical Technology Letters, 62, 3051-3059(2020).
[15] Xu Y J, Li C. Light-weight object detection network optimized based on YOLO family[J]. Computer Science, 48, 265-269(2021).
[16] Jiang R Q, Peng Y P, Xie W X et al. Improved YOLOv4 small target detection algorithm with embedded scSE module[J]. Journal of Graphics, 42, 546-555(2021).
[18] Zheng Z H, Wang P, Liu W et al. Distance-IoU loss: faster and better learning for bounding box regression[J]. Proceedings of the AAAI Conference on Artificial Intelligence, 34, 12993-13000(2020).
[20] Woo S, Park J, Lee J Y et al. CBAM: convolutional block attention module[M]. Ferrari V, Hebert M, Sminchisescu C, et al. Computer vision-ECCV 2018. Lecture notes in computer science, 11211, 3-19(2018).
[21] Sandler M, Howard A, Zhu M L et al. MobileNetV2: inverted residuals and linear bottlenecks[C], 4510-4520(2018).
[22] Qiao S Y, Chen L C, Yuille A. DetectoRS: detecting objects with recursive feature pyramid and switchable atrous convolution[C], 10208-10219(2021).
[23] Yang M K, Yu K, Zhang C et al. DenseASPP for semantic segmentation in street scenes[C], 3684-3692(2018).