[1] Ruijian Du, Baozhen Ge, Lei Chen. Texture mapping of multi-view high-resolution images and binocular 3D point clouds. Chinese Optics, 13, 1055-1064(2020).
[2] Yu Wei, Shilei Jiang, Guobin Sun, et al. Design of solid-state array laser radar receiving optical system. Chinese Optics, 13, 517-526(2020).
[3] Yong Li, Guofeng Tong, Jingchao Yang, et al. 3D point cloud scene data acquisition and its key technology for scene understanding. Laser & Optoelectronics Progress, 56, 13-26(2019).
[4] Xitong Zhang, Yongqiang Li, Jie Mao, et al. Segmentation of connected street trees from mobile LiDAR data. Science of Surveying and Mapping, 41, 111-115(2016).
[5] Yicong Feng, Minyi Cen, Tonggang Zhang. Knowledge-based automatic objects classification from mobile LiDAR data. Computer Engineering and Applications, 52, 122-126(2016).
[6] Yuxing Xie, Jiaojiao Tian, Xiaoxiang Zhu. Linking points with labels in 3D: A review of point cloud semantic segmentation. IEEE Geoence and Remote Sensing Magazine, 8, 38-59(2020).
[7] M Weinmann, B Jutzi, S Hinz, et al. Semantic point cloud interpretation based on optimal neighborhoods, relevant features and efficient classifiers. ISPRS Journal of Photogrammetry and Remote Sensing, 105, 286-304(2015).
[8] Haiting Li, Houzhi Wang, Yanhong Li, et al. Object recognition for vehicle-borne LiDAR point clouds based on SVM. Science of Surveying and Mapping, 41, 45-49(2016).
[9] Zhiqing Liu, Pengcheng Li, Haitao Guo, et al. Airborn LiDAR point cloud data classification based on relevance vector machine. Infrared and Laser Engineering, 45, S130006(2016).
[10] Guofeng Tong, Xiance Du, Yong. Li et al. Three-dinmensional point cloud classification of large outdoor scenes based on vertical slice sampling and centroid distance histogram. Chinese Journal of Lasers, 45, 1004001(2018).
[11] B Xiang, J Yao, X Lu, et al. Segmentation-based classification for 3D point clouds in the road environment. International Journal of Remote Sensing, 39, 6182-6212(2018).
[12] Yong Tang, Zheng Xiang, Tengping Jiang, et al. Semantic classification of pole-like traffic facilities in complex road scenes based on LiDAR point cloud. Tropical Geography, 40, 893-902(2020).
[13] Pengpeng Li, Yongqiang Li, Shangbin Zhao, et al. Automatic classification of pole-like objects in road scene by back propagation neural network. Bulletin of Surveying and Mapping, 101-105, 120(2020).
[14] Zhongyu Zhang, Yunpeng Liu, Sikui Wang, et al. Vehicle target recognition algorithm for UAV image based on DRFP. Infrared and Laser Engineering, 48, S226001(2019).
[15] Xinkai Liang, Chuang Song, Jiajia Zhao. Depth estimation technique of sequence image based on deep learning. Infrared and Laser Engineering, 48, S226002(2019).
[16] Qili Yang, Binghong Zhou, Wei Zheng, et al. Trajectory detection of small targets based on convolutional long short-term memory with attention mechanisms. Optics and Precision Engineering, 28, 2535-2548(2020).
[17] Milioto A, Vizzo I, Behley J, et al. Range++: Fast accurate LiDAR semantic segmentation[C]2019 IEEERSJ International Conference on Intelligent Robots Systems (IROS). IEEE, 2019: 42134220.
[18] Graham B, Engelcke M, Van Der Maaten L. 3D semantic segmentation with submanifold sparse convolutional wks[C]Proceedings of the IEEE Conference on Computer Vision Pattern Recognition, 2018: 92249232.
[19] Meng H Y, Gao L, Lai Y K, et al. Vv: Voxel vae with group convolutions f point cloud segmentation[C]Proceedings of the IEEE International Conference on Computer Vision, 2019: 85008508.
[20] Yue Wang, Yongbin Sun, Ziwei Liu, et al. Dynamic graph cnn for learning on point clouds. ACM Transactions on Graphics, 38, 1-12(2019).
[21] L Ma, Y Li, J Li, et al. Multi-scale point-wise convolutional neural networks for 3D object segmentation from LiDAR point clouds in large-scale environments. IEEE Transactions on Intelligent Transportation Systems, 22, 821-836(2019).
[22] Hu Q, Yang B, Xie L, et al. RLA: Efficient semantic segmentation of largescale point clouds[C]2020 IEEECVF Conference on Computer Vision Pattern Recognition (CVPR), IEEE, 2020: 1110511114.
[23] M Feng, L Zhang, X Lin, et al. Point attention network for semantic segmentation of 3D point clouds. Pattern Recognition, 107, 107446(2020).
[24] Jun Yang, Jisheng Dang. Recognition and segmentation of three-dimensional point cloud based on deep cascade convolutional neural network. Optics and Precision Engineering, 28, 1187-1199(2020).
[25] Lrieu L, Simonovsky M. Largescale point cloud semantic segmentation with superpoint graphs[C]Proceedings of the IEEE Conference on Computer Vision Pattern Recognition, 2018: 45584567.
[26] Ester M, Kriegel H P, Ser J, et al. Densitybased spatial clustering of applications with noise[C]Proceedings of 2nd International Conference on Knowledge Discovery Data Mining, 1996, 240: 6.