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Bird's-Eye-View Semantic Segmentation With Two-Stream Compact Depth Transformation and Feature Rectification 期刊论文
IEEE TRANSACTIONS ON INTELLIGENT VEHICLES, 2023, 卷号: 8, 期号: 11, 页码: 4546-4558
作者:  Liu, Jierui;  Cao, Zhiqiang;  Yang, Jing;  Liu, Xilong;  Yang, Yuequan;  Qu, Zhiyou
Adobe PDF(21890Kb)  |  收藏  |  浏览/下载：57/6  |  提交时间：2024/03/27
Bird's-eye-view  semantic segmentation  two-stream compact depth transformation  feature rectification  
GAN-Based Facial Attribute Manipulation 期刊论文
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2023, 卷号: 45, 期号: 12, 页码: 14590-14610
作者:  Liu, Yunfan;  Li, Qi;  Deng, Qiyao;  Sun, Zhenan;  Yang, Ming-Hsuan
Adobe PDF(15297Kb)  |  收藏  |  浏览/下载：66/18  |  提交时间：2024/02/22
Generative adversarial networks  image translation  facial attribute manipulation  
Key-Part Attention Retrieval for Robotic Object Recognition 期刊论文
TSINGHUA SCIENCE AND TECHNOLOGY, 2024, 卷号: 29, 期号: 3, 页码: 644-655
作者:  Liu, Jierui;  Cao, Zhiqiang;  Tang, Yingbo
Adobe PDF(2164Kb)  |  收藏  |  浏览/下载：79/6  |  提交时间：2024/02/22
Training  Visualization  Image recognition  Cameras  Object recognition  Convolutional neural networks  Data mining  key-part attention  retrieval  robotic object recognition  
A Graded Assessment System for Parkinsons Upper-Limb Bradykinesia Based on a Temporal Convolutional Network Model 期刊论文
IEEE SENSORS JOURNAL, 2023, 卷号: 23, 期号: 23, 页码: 29283-29292
作者:  Tong, Lina;  Liu, Dai-Song;  Peng, Liang;  Hao, Hong-Lin;  Wang, Chen
Adobe PDF(9425Kb)  |  收藏  |  浏览/下载：44/2  |  提交时间：2024/02/21
Bradykinesia grade  inertial sensors  Parkinson's disease (PD)  temporal convolutional network (TCN)  wearable device  
Accurate Lung Nodule Segmentation With Detailed Representation Transfer and Soft Mask Supervision 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2023, 页码: 13
作者:  Wang, Changwei;  Xu, Rongtao;  Xu, Shibiao;  Meng, Weiliang;  Xiao, Jun;  Zhang, Xiaopeng
Adobe PDF(4178Kb)  |  收藏  |  浏览/下载：131/6  |  提交时间：2023/12/21
Detailed representation transfer  lung nodules segmentation  medical images segmentation  soft mask  
A learnable EEG channel selection method for MI-BCI using efficient channel attention 期刊论文
FRONTIERS IN NEUROSCIENCE, 2023, 卷号: 17, 页码: 13
作者:  Tong, Lina;  Qian, Yihui;  Peng, Liang;  Wang, Chen;  Hou, Zeng-Guang
Adobe PDF(2021Kb)  |  收藏  |  浏览/下载：69/3  |  提交时间：2023/12/21
brain-computer interface  motor imagery  channel selection  deep learning  attention mechanism  
IDO: Instance dual-optimization for weakly supervised object detection 期刊论文
APPLIED INTELLIGENCE, 2023, 页码: 18
作者:  Ren, Zhida;  Tang, Yongqiang;  Zhang, Wensheng
Adobe PDF(3668Kb)  |  收藏  |  浏览/下载：55/2  |  提交时间：2023/11/17
Deep learning  Weakly supervised learning  Object detection  Multiple instance learning  
Attention Weighted Local Descriptors 期刊论文
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2023, 卷号: 45, 期号: 9, 页码: 10632-10649
作者:  Wang, Changwei;  Xu, Rongtao;  Lu, Ke;  Xu, Shibiao;  Meng, Weiliang;  Zhang, Yuyang;  Fan, Bin;  Zhang, Xiaopeng
Adobe PDF(8075Kb)  |  收藏  |  浏览/下载：143/4  |  提交时间：2023/11/17
Local features detection and description  consistent attention mechanism  context augmentation  lightweight local descriptors  knowledge distillation  
Toward Accurate and Efficient Road Extraction by Leveraging the Characteristics of Road Shapes 期刊论文
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2023, 卷号: 61, 页码: 16
作者:  Wang, Changwei;  Xu, Rongtao;  Xu, Shibiao;  Meng, Weiliang;  Wang, Ruisheng;  Zhang, Jiguang;  Zhang, Xiaopeng
Adobe PDF(13777Kb)  |  收藏  |  浏览/下载：115/4  |  提交时间：2023/11/17
Efficient and accurate road extraction  efficient strip transformer module (ESTM)  geometric deformation estimation module (GDEM)  road edge focal loss (REF loss)  road shape-aware network (RSANet)  
Identifying the key frames: An attention-aware sampling method for action recognition 期刊论文
PATTERN RECOGNITION, 2022, 卷号: 130, 页码: 11
作者:  Dong, Wenkai;  Zhang, Zhaoxiang;  Song, Chunfeng;  Tan, Tieniu
收藏  |  浏览/下载：39/0  |  提交时间：2023/11/17
Action recognition  Deep learning  Reinforcement learning  Pseudo labels