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Efficient Pairwise 3-D Registration of Urban Scenes via Hybrid Structural Descriptors 期刊论文
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2021, 页码: 17
作者:  Zhang, Long;  Guo, Jianwei;  Cheng, Zhanglin;  Xiao, Jun;  Zhang, Xiaopeng
Adobe PDF(13657Kb)  |  收藏  |  浏览/下载：270/6  |  提交时间：2022/01/27
Three-dimensional displays  Shape  Feature extraction  Semantics  Robustness  Cloud computing  Virtual reality  Descriptor  hybrid structure  point cloud  registration  urban scene  
ECBC: Efficient Convolution via Blocked Columnizing 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2021, 页码: 13
作者:  Zhao, Tianli;  Hu, Qinghao;  He, Xiangyu;  Xu, Weixiang;  Wang, Jiaxing;  Leng, Cong;  Cheng, Jian
Adobe PDF(3003Kb)  |  收藏  |  浏览/下载：335/41  |  提交时间：2022/01/27
Convolution  Tensors  Layout  Memory management  Indexes  Transforms  Performance evaluation  Convolutional neural networks (CNNs)  direct convolution  high performance computing for mobile devices  im2col convolution  memory-efficient convolution (MEC)  
Quantum superposition inspired spiking neural network 期刊论文
ISCIENCE, 2021, 卷号: 24, 期号: 8, 页码: 16
作者:  Sun, Yinqian;  Zeng, Yi;  Zhang, Tielin
Adobe PDF(2756Kb)  |  收藏  |  浏览/下载：261/46  |  提交时间：2021/11/03
Extremely Lightweight Skeleton-Based Action Recognition With ShiftGCN plus 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2021, 卷号: 30, 页码: 7333-7348
作者:  Cheng, Ke;  Zhang, Yifan;  He, Xiangyu;  Cheng, Jian;  Lu, Hanqing
Adobe PDF(3205Kb)  |  收藏  |  浏览/下载：297/16  |  提交时间：2021/11/03
Skeleton-based action recognition  graph convolutional network  lightweight network  shift network  
GA-NET: Global Attention Network for Point Cloud Semantic Segmentation 期刊论文
IEEE SIGNAL PROCESSING LETTERS, 2021, 卷号: 28, 页码: 1300-1304
作者:  Deng, Shuang;  Dong, Qiulei
Adobe PDF(801Kb)  |  收藏  |  浏览/下载：215/40  |  提交时间：2021/08/15
Three-dimensional displays  Feature extraction  Semantics  Computational complexity  Vegetation mapping  Image segmentation  Feeds  3D point cloud  semantic segmentation  global attention  convolutional neural networks  deep learning