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LA-Net: layer attention network for 3D-to-2D retinal vessel segmentation in OCTA images 期刊论文
PHYSICS IN MEDICINE AND BIOLOGY, 2024, 卷号: 69, 期号: 4, 页码: 15
作者:  Yang, Chaozhi;  Li, Bei;  Xiao, Qian;  Bai, Yun;  Li, Yachuan;  Li, Zongmin;  Li, Hongyi;  Li, Hua
收藏  |  浏览/下载：11/0  |  提交时间：2024/05/20
retinal vessel segmentation  3D-to-2D  multi-scale layer attention  reverse boundary attention  OCTA volume  
Multi-scale conditional reconstruction generative adversarial network 期刊论文
IMAGE AND VISION COMPUTING, 2024, 卷号: 141, 页码: 9
作者:  Chen, Yanming;  Xu, Jiahao;  An, Zhulin;  Zhuang, Fuzhen
收藏  |  浏览/下载：9/0  |  提交时间：2024/05/20
Generative adversarial network  Unsupervised generation  Multi-scale instance  Reconstructed losses  
Improving the Scalability of Distributed Network Emulations: An Algorithmic Perspective 期刊论文
IEEE TRANSACTIONS ON NETWORK AND SERVICE MANAGEMENT, 2023, 卷号: 20, 期号: 4, 页码: 4325-4339
作者:  Zhao, Huaiyi;  Zhang, Xinyi;  Wang, Yang;  Diao, Zulong;  Li, Yanbiao;  Xie, Gaogang
收藏  |  浏览/下载：7/0  |  提交时间：2024/05/20
Distributed network emulations  service assurance  performance evaluations  large-scale experimental platforms  optimization theories  multilevel algorithms  
Large Scale Visual Food Recognition 期刊论文
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2023, 卷号: 45, 期号: 8, 页码: 9932-9949
作者:  Min, Weiqing;  Wang, Zhiling;  Liu, Yuxin;  Luo, Mengjiang;  Kang, Liping;  Wei, Xiaoming;  Wei, Xiaolin;  Jiang, Shuqiang
收藏  |  浏览/下载：13/0  |  提交时间：2023/12/04
Image recognition  Visualization  Task analysis  Benchmark testing  Representation learning  Training  Semantics  Food dataset  food recognition  large-scale datasets  fine-grained recognition  
Toward Developing High-Performance RISC-V Processors Using Agile Methodology 期刊论文
IEEE MICRO, 2023, 卷号: 43, 期号: 4, 页码: 98-106
作者:  Xu, Yinan;  Yu, Zihao;  Tang, Dan;  Cai, Ye;  Huan, Dandan;  He, Wei;  Sun, Ninghui;  Bao, Yungang
收藏  |  浏览/下载：13/0  |  提交时间：2023/12/04
Program processors  Behavioral sciences  Chip scale packaging  Microarchitecture  Hardware  Analytical models  Layout  
Importance First: Generating Scene Graph of Human Interest 期刊论文
INTERNATIONAL JOURNAL OF COMPUTER VISION, 2023, 页码: 27
作者:  Wang, Wenbin;  Wang, Ruiping;  Shan, Shiguang;  Chen, Xilin
收藏  |  浏览/下载：12/0  |  提交时间：2023/12/04
Key relationship  Hierarchical entity tree  Hierarchical contextual propagation  Relationship ranking  Spatial scale  Visual saliency  
Multiscale Mesh Deformation Component Analysis With Attention-Based Autoencoders 期刊论文
IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS, 2023, 卷号: 29, 期号: 2, 页码: 1301-1317
作者:  Yang, Jie;  Gao, Lin;  Tan, Qingyang;  Huang, Yi-Hua;  Xia, Shihong;  Lai, Yu-Kun
收藏  |  浏览/下载：19/0  |  提交时间：2023/07/12
Multi-scale  shape analysis  attention mechanism  sparse regularization  stacked auto-encoder  
DRONE: An Efficient Distributed Subgraph-Centric Framework for Processing Large-Scale Power-law Graphs 期刊论文
IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS, 2023, 卷号: 34, 期号: 2, 页码: 463-474
作者:  Zhang, Shuai;  Jiang, Zite;  Hou, Xingzhong;  Li, Mingyu;  Yuan, Mengting;  You, Haihang
收藏  |  浏览/下载：20/0  |  提交时间：2023/07/12
Fault tolerance  graph partition  large-scale power-law graph  parallel graph computation  subgraph-centric model  
Spatial-Temporal Graph Network for Video Crowd Counting 期刊论文
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, 2023, 卷号: 33, 期号: 1, 页码: 228-241
作者:  Wu, Zhe;  Zhang, Xinfeng;  Tian, Geng;  Wang, Yaowei;  Huang, Qingming
收藏  |  浏览/下载：20/0  |  提交时间：2023/07/12
Computational modeling  Predictive models  Analytical models  Long short term memory  Optical flow  Integrated circuit modeling  Head  Video-based crowd counting  spatiotemporal graph attention  multi-scale module  
SMNet: Synchronous Multi-Scale Low Light Enhancement Network With Local and Global Concern 期刊论文
IEEE TRANSACTIONS ON MULTIMEDIA, 2023, 卷号: 25, 页码: 9506-9517
作者:  Lin, Shideng;  Tang, Fan;  Dong, Weiming;  Pan, Xingjia;  Xu, Changsheng
收藏  |  浏览/下载：7/0  |  提交时间：2024/05/20
Low-light image enhancement  multi-scale feature learning  deep-learning