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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：60/0  |  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  
Narrowing the Gap: Improved Detector Training With Noisy Location Annotations 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2022, 卷号: 31, 页码: 6369-6380
作者:  Wang, Shaoru;  Gao, Jin;  Li, Bing;  Hu, Weiming
Adobe PDF(1489Kb)  |  收藏  |  浏览/下载：218/26  |  提交时间：2022/11/14
Annotations  Noise measurement  Detectors  Task analysis  Training  Object detection  Degradation  Object detection  noisy label  Bayesian estimation  teacher-student learning  
PDNet: Toward Better One-Stage Object Detection With Prediction Decoupling 期刊论文
IEEE Transactions on Image Processing, 2022, 卷号: 31, 页码: 5121-5133
作者:  Yang, Li;  Xu, Yan;  Wang, Shaoru;  Yuan, Chunfeng;  Zhang, Ziqi;  Li, Bing;  Hu, Weiming
Adobe PDF(3190Kb)  |  收藏  |  浏览/下载：253/35  |  提交时间：2022/09/19
Object detection  prediction decoupling  convolutional neural network  
Holographic Feature Learning of Egocentric-Exocentric Videos for Multi-Domain Action Recognition 期刊论文
IEEE TRANSACTIONS ON MULTIMEDIA, 2022, 卷号: 24, 页码: 2273-2286
作者:  Huang, Yi;  Yang, Xiaoshan;  Gao, Junyun;  Xu, Changsheng
Adobe PDF(2409Kb)  |  收藏  |  浏览/下载：337/65  |  提交时间：2022/07/25
Videos  Feature extraction  Visualization  Task analysis  Computational modeling  Target recognition  Prototypes  Egocentric videos  exocentric videos  holographic feature  multi-domain  action recognition  
Deep Self-Evolution Clustering 期刊论文
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2020, 卷号: 42, 期号: 4, 页码: 809-823
作者:  Chang, Jianlong;  Meng, Gaofeng;  Wang, Lingfeng;  Xiang, Shiming;  Pan, Chunhong
浏览  |  Adobe PDF(4817Kb)  |  收藏  |  浏览/下载：413/90  |  提交时间：2020/06/02
Task analysis  Unsupervised learning  Training  Clustering methods  Pattern analysis  Clustering  deep self-evolution clustering  self-evolution clustering training  deep unsupervised learning  
Spatial non-local attention for thoracic disease diagnosis and visualisation in weakly supervised learning 期刊论文
IET IMAGE PROCESSING, 2019, 卷号: 13, 期号: 11, 页码: 1922-1930
作者:  Yang, Menglin;  Li, Ding;  Zhang, Wensheng
收藏  |  浏览/下载：304/0  |  提交时间：2019/12/16
feature extraction  diseases  medical image processing  patient diagnosis  image segmentation  image classification  supervised learning  image annotation  thoracic disease diagnosis  weakly supervised learning  computer-aided diagnosis  coarse image-level annotations  pathological area  nonlocal aware features  fine-grained expertise  clinical diagnosis  visualisation method  chest X-ray dataset  spatial nonlocal attention mechanism  ResNet-SNA