中文版 | English

在结果中检索

CASIA OpenIR

浏览/检索结果: 共15条，第1-10条 帮助

限定条件        
已选(0)清除 条数/页：   排序方式：
IterDepth: Iterative Residual Refinement for Outdoor Self-Supervised Multi-Frame Monocular Depth Estimation 期刊论文
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, 2024, 卷号: 34, 期号: 1, 页码: 329-341
作者:  Feng, Cheng;  Chen, Zhen;  Zhang, Congxuan;  Hu, Weiming;  Li, Bing;  Lu, Feng
收藏  |  浏览/下载：21/0  |  提交时间：2024/03/26
Estimation  Iterative methods  Cameras  Task analysis  Feature extraction  Decoding  Training  Monocular depth estimation  iterative refinement  self-supervised learning  deep learning  
Learning Gait Representation From Massive Unlabelled Walking Videos: A Benchmark 期刊论文
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2023, 卷号: 45, 期号: 12, 页码: 14920-14937
作者:  Fan, Chao;  Hou, Saihui;  Wang, Jilong;  Huang, Yongzhen;  Yu, Shiqi
收藏  |  浏览/下载：21/0  |  提交时间：2024/03/26
Gait recognition  self-supervised  contrastive learning  GaitSSB  GaitLU-1M  
Bridging the gap with grad: Integrating active learning into semi-supervised domain generalization 期刊论文
NEURAL NETWORKS, 2024, 卷号: 171, 页码: 186-199
作者:  Li, Jingwei;  Li, Yuan;  Tan, Jie;  Liu, Chengbao
收藏  |  浏览/下载：22/0  |  提交时间：2024/03/26
Domain generalization  Semi-supervised learning  Active learning  
Multi-Cue Guided Semi-Supervised Learning Toward Target Speaker Separation in Real Environments 期刊论文
IEEE-ACM TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING, 2024, 卷号: 32, 页码: 151-163
作者:  Xu, Jiaming;  Cui, Jian;  Hao, Yunzhe;  Xu, Bo
收藏  |  浏览/下载：47/0  |  提交时间：2024/02/22
Cocktail party problem  target speaker separation  multi-cue guided separation  semi-supervised learning  
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
收藏  |  浏览/下载：37/0  |  提交时间：2023/11/17
Deep learning  Weakly supervised learning  Object detection  Multiple instance learning  
Seeing Through Darkness: Visual Localization at Night via Weakly Supervised Learning of Domain Invariant Features 期刊论文
IEEE TRANSACTIONS ON MULTIMEDIA, 2023, 卷号: 25, 页码: 1713-1726
作者:  Fan, Bin;  Yang, Yuzhu;  Feng, Wensen;  Wu, Fuchao;  Lu, Jiwen;  Liu, Hongmin
收藏  |  浏览/下载：92/0  |  提交时间：2023/11/17
Domain invariant local features  image matching  long-term visual localization  weakly supervised learning  
ATF: An Alternating Training Framework for Weakly Supervised Face Alignment 期刊论文
IEEE TRANSACTIONS ON MULTIMEDIA, 2023, 卷号: 25, 页码: 1798-1809
作者:  Lan, Xing;  Hu, Qinghao;  Cheng, Jian
收藏  |  浏览/下载：50/0  |  提交时间：2023/11/17
Face alignment  multi-task learning  weakly supervised  
Online Progressive Instance-Balanced Sampling for Weakly Supervised Vibration Damper Detection 期刊论文
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 2023, 卷号: 72, 页码: 14
作者:  Chen, Minghao;  Tian, Yunong;  Li, Zhishuo;  Li, En;  Liang, Zize
收藏  |  浏览/下载：78/0  |  提交时间：2023/11/17
Shock absorbers  Vibrations  Object detection  Proposals  Training  Sampling methods  Convolutional neural networks  Instance balance  multiple instance learning (MIL)  progressive sampling  vibration damper detection  weakly supervised object detection (WSOD)  
A Semisupervised End-to-End Framework for Transportation Mode Detection by Using GPS-Enabled Sensing Devices 期刊论文
IEEE INTERNET OF THINGS JOURNAL, 2022, 卷号: 9, 期号: 10, 页码: 7842-7852
作者:  Li, Zhishuai;  Xiong, Gang;  Wei, Zebing;  Lv, Yisheng;  Anwar, Noreen;  Wang, Fei-Yue
收藏  |  浏览/下载：203/0  |  提交时间：2022/07/25
GPS trajectory  human mobility  semi-supervised learning  transportation mode detection (TMD)  
Self-Supervised Contact Geometry Learning by GelStereo Visuotactile Sensing 期刊论文
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 2022, 卷号: 71, 页码: 9
作者:  Cui, Shaowei;  Wang, Rui;  Hu, Jingyi;  Zhang, Chaofan;  Chen, Lipeng;  Wang, Shuo
Adobe PDF(1925Kb)  |  收藏  |  浏览/下载：569/297  |  提交时间：2022/06/06
Geometry  Sensors  Three-dimensional displays  Estimation  Image reconstruction  Tactile sensors  Color  Depth estimation  robotic sensing systems  self-supervised learning  tactile sensors