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293 results on '"ZHANG Xingzhong"'

2. An Energy Sampling Replay-Based Continual Learning Framework

Author

Zhang, Xingzhong, Chuah, Joon Huang, Loo, Chu Kiong, Wermter, Stefan, Goos, Gerhard, Series Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Wand, Michael, editor, Malinovská, Kristína, editor, Schmidhuber, Jürgen, editor, and Tetko, Igor V., editor

Published
2024
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37. A Multi-factor Recommendation Algorithm for POI Recommendation

Author

Yang, Rong, Han, Xiaofeng, Zhang, Xingzhong, Hutchison, David, Series Editor, Kanade, Takeo, Series Editor, Kittler, Josef, Series Editor, Kleinberg, Jon M., Series Editor, Mattern, Friedemann, Series Editor, Mitchell, John C., Series Editor, Naor, Moni, Series Editor, Pandu Rangan, C., Series Editor, Steffen, Bernhard, Series Editor, Terzopoulos, Demetri, Series Editor, Tygar, Doug, Series Editor, Meng, Xiaofeng, editor, Li, Ruixuan, editor, Wang, Kanliang, editor, Niu, Baoning, editor, Wang, Xin, editor, and Zhao, Gansen, editor

Published
2018
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43. Comparative analysis of surface deformation monitoring in a mining area based on UAV‐lidar and UAV photogrammetry.

Author

Zhan, Xilin, Zhang, Xingzhong, Wang, Xiao, Diao, Xinpeng, and Qi, Lizhuan

Subjects
*DEFORMATION of surfaces, *OPTICAL radar, *LIDAR, *SURFACE analysis, *PHOTOGRAMMETRY, *DRONE aircraft
Abstract

Unmanned aerial vehicle light detection and ranging (UAV‐lidar) and unmanned aerial vehicle (UAV) photogrammetry are currently commonly used surface monitoring technologies. Previous studies have used the two technologies interchangeably and ignored their correlation, or only compared them on a single product. However, there are few quantitative assessments of the differences between these two techniques in monitoring surface deformation and prediction of their application prospects. Therefore, the paper compared the differences between the digital elevation model (DEM) and subsidence basins obtained by the two techniques using Gaussian analysis. The results indicate that the surface DEMs obtained by both the techniques exhibit a high degree of similarity. The statistical analysis of the difference values in the z direction between the two DEMs follows a Gaussian distribution with a standard deviation of less than 0.36 m. When comparing the surface subsidence values monitored by the two techniques, it was found that UAV‐lidar was more sensitive to small‐scale deformation, with a difference range of 0.23–0.44 m compared to photogrammetry. The conclusion provides valuable information regarding the utilisation of multisource monitoring data. [ABSTRACT FROM AUTHOR]

Published
2024
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44. 3D Object Detection in Substation Scene Based on Voxelization.

Author

WANG Dawei, HU Fan, ZHANG Na, YANG Gang, LU Jiyuan, and ZHANG Xingzhong

Subjects
OBJECT recognition (Computer vision), FEATURE extraction
Abstract

Aiming at the problem of low detection accuracy caused by insufficient target feature extraction in substation 3D scene, a voxelization-based 3D object detection model AugSecond for substation scene is proposed, which is designed based on the Second network structure. It introduces a triple attention mechanism in the voxel feature encoding stage, which focuses on multi-dimensional attention to enhance the key information of the target and reduce the interference of irrelevant feature information. It designes asymmetric sparse convolutional networks, uses asymmetric convolution to improve convolutional kernel representation capabilities and fuses multi-scale features to enrich target geometry information. Meanwhile, the position regression loss is optimized, and CIoU Loss is used to further consider the geometric correlation between bounding boxes to speed up the network convergence. Experiments on self-built power scene data sets and public data sets show that compared with the benchmark model, AugSecond model significantly improves recognition accuracy and has real-time reasoning speed, which proves the effectiveness of the proposed model. [ABSTRACT FROM AUTHOR]

Published
2024
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