[1] Hao Deng, Wei Zheng, Mingtao Li, et al. Dim moving target detection based on fluctuation analysis. Optics and Precision Engineering, 28, 2517-2526(2020).
[2] Dezhen Yang, Songlin Yu, Jinjun Feng, et al. Low false alarm infrared target detection in airborne complex scenes. Optics and Precision Engineering, 30, 96-107(2022).
[3] Shanshan Song, Xuping Zhai. Improved infrared anomaly target detection algorithm based on single Gaussian model. Infrared Technology, 43, 885-888, 894(2021).
[4] Rong Zhen, Ziqiang Shi. Ship trajectory clustering method based on Gaussian mixture model. Ship Engineering, 43, 139-143(2021).
[5] Min’an Tang, Chenyu Wang. Moving object detection in static scene base on improved vibe algorithm. Laser & Opto-electronics Progress, 58, 1410011(2021).
[6] L Liu, G H Chai, Z Qu. Moving target detection based on improved ghost suppression and adaptive visual background extraction. Journal of Central South University, 28, 747-759(2021).
[7] Peng Sun, Yue Yu, Jiaxin Chen, et al. Highly dynamic aerial polymorphic target detection method based on deep spatial-temporal feature fusion (Invited). Infrared and Laser Engineering, 51, 20220167(2022).
[8] Yang H Z. Research on real time target clustering recognition of LiDAR point cloud f autonomous driving[D]. Hefei: University of Science Technology of China, 2021. (in Chinese)
[9] Yuan H N, Sun W, Xiang T Y. Line laser point cloud segmentation based on the combination of RANSAC region growing[C]Proceedings of the 39th Chinese Control Conference, 2020: 63246328.
[10] Maturana D, Scherer S. Vox: A 3D Convolutional Neural wk f realtime object recognition[C]International Conference on Intelligent Robots Systems(IROS). IEEE, 2015: 922928.
[11] Qi C R, Yi L, Su H, et al. Point++: Deep hierarchical feature learning on point sets in a metric space[C]Advances in Neural Infmation Processing Systems, 2017: 50995108.
[12] Ruiyan Zhang, Xiujie Jiang, Junshe An, et al. Design of global-contextual detection model for optical remote sensing targets. Chinese Optics, 13, 1302-1313(2020).
[13] Shi S H, Wang X G , Li H S. PointRCNN: 3D object proposal generation detection from point cloud[C]Proceedings of the IEEE Conference on Computer Vision Pattern Recognition (CVPR), Long Beach: IEEE, 2019: 770779.
[14] S Q Ren, K M He, R Girshick, et al. Faster R-CNN: towards real-time object detection with region proposal networks. IEEE Transactions on Pattern Analysis and Machine Intelligence, 39, 1137-1149(2017).
[15] Redmon J, Farhadi A. YOLOv3: An Incremental Improvement[EBOL]. (20180408)[2022−10−09]. https:arxiv.gabs1804.02767.
[16] Liu W, Anguelov D, Erhan D, et al. SSD: single shot multibox detect[C]European Conference on Computer Vision (ECCV). Amsterdam, The herls: Springer, 2016: 2137.
[17] Yong Bi, Mingqi Pan, Shuo Zhang, et al. Overview of 3D point cloud super-resolution technology. Chinese Optics, 15, 210-223(2022).
[18] Geiger A, Lenz P, Urtasun R. Are we ready f autonomous driving The KITTI Vision benchmark suite[C]IEEE Conference on Computer Vision & Pattern Recognition (CVPR), Providence, RI, USA. New Yk: IEEE, 2012: 33543361.
[19] A Geiger, P Lenz, C Stiller, et al. Vision meets robotics: The KITTI Dataset. International Journal of Robotics Research, 32, 1231-1237(2013).
[20] Ye Shi, Xiaokai Wang, Huifeng Liu. Research on bilateral filtering algorithm base on local filtering template. Journal of Test and Measurement Technology, 35, 49-53(2021).
[21] Chengbin Xing, Shengsheng Gong, Xiaoliang Yu, et al. Application of Gaussian mixture clustering to moving surface fitting filter classification. Infrared and Laser Engineering, 50, 20200501(2021).
[22] R Nitzberg. Clutter map CFAR analysisl. IEEE Transactions on Aerospace and Electronic Systems, 22, 419-421(1986).
[23] Chao Ban, Weilin Pan, Rui Wang, et al. Initial results of Rayleigh scattering lidar observations at Zhongshan station, Antarctica. Infrared and Laser Engineering, 50, 20210010(2021).