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Deep Learning-based Moving Object Segmentation: Recent Progress and Research Prospects 期刊论文
Machine Intelligence Research, 2023, 卷号: 20, 期号: 3, 页码: 335-369
作者:  Rui Jiang;  Ruixiang Zhu;  Hu Su;  Yinlin Li;  Yuan Xie;  Wei Zou
Adobe PDF(9061Kb)  |  收藏  |  浏览/下载：2/0  |  提交时间：2024/04/23
Moving object segmentation (MOS), change detection, background subtraction, deep learning (DL), video understanding  
3D Scanning of High Dynamic Scenes Using an RGB-D Sensor and an IMU on a Mobile Device 期刊论文
IEEE Access, 2019, 期号: 7, 页码: 24057-24070
作者:  Liu, Yangdong;  Gao, Wei;  Hu, Zhanyi
浏览  |  Adobe PDF(4113Kb)  |  收藏  |  浏览/下载：233/79  |  提交时间：2019/05/08
Dynamic Scenes  Background Segmentation  Rgb-d  Mobile Device  
Real-time segmentation of various insulators using generative adversarial networks 期刊论文
IET COMPUTER VISION, 2018, 卷号: 12, 期号: 5, 页码: 596-602
作者:  Chang, Wenkai;  Yang, Guodong;  Yu, Junzhi;  Liang, Zize
Adobe PDF(4584Kb)  |  收藏  |  浏览/下载：394/66  |  提交时间：2019/12/16
image segmentation  insulators  neural nets  power engineering computing  real-time pixel-level segmentation  generative adversarial networks  insulator segmentation algorithm  cluttered background  artificial thresholds  compact end-to-end neural network  visual saliency map  proposed two-stage training  segmentation quality  
High-Performance Video Condensation System 期刊论文
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, 2015, 卷号: 25, 期号: 7, 页码: 1113-1124
作者:  Zhu, Jianqing;  Feng, Shikun;  Yi, Dong;  Liao, Shengcai;  Lei, Zhen;  Li, Stan Z.
Adobe PDF(3439Kb)  |  收藏  |  浏览/下载：290/66  |  提交时间：2015/09/23
Gpu Acceleration  Moving Object Segmentation  Online Background Generation  Video Condensation System  Video Storage  Video Surveillance  
Conditional random field for text segmentation from images with complex background 期刊论文
PATTERN RECOGNITION LETTERS, 2010, 卷号: 31, 期号: 14, 页码: 2295-2308
作者:  Li, Minhua;  Bai, Meng;  Wang, Chunheng;  Xiao, Baihua
收藏  |  浏览/下载：151/0  |  提交时间：2015/08/12
Conditional Random Field (Crf)  Text Segmentation  Complex Background  Local Information  Contextual Label Information