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Directional Deep Embedding and Appearance Learning for Fast Video Object Segmentation 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2021, 页码: 11
作者:  Yin, Yingjie;  Xu, De;  Wang, Xingang;  Zhang, Lei
收藏  |  浏览/下载：216/0  |  提交时间：2022/02/16
Feature extraction  Kernel  Object segmentation  Faces  Probabilistic logic  Learning systems  Image segmentation  Deep appearance learning  directional deep embedding learning  directional statistics-based learning  video object segmentation (VOS)  
GPENs: Graph Data Learning With Graph Propagation-Embedding Networks 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2021, 页码: 14
作者:  Jiang, Bo;  Wang, Leiling;  Cheng, Jian;  Tang, Jin;  Luo, Bin
收藏  |  浏览/下载：214/0  |  提交时间：2022/01/27
Task analysis  Computer architecture  Semisupervised learning  Deep learning  Laplace equations  Data models  Labeling  Graph embedding  graph neural networks (GNNs)  graph propagation  semi-supervised learning  
A Novel Pixel-Wise Defect Inspection Method Based on Stable Background Reconstruction 期刊论文
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 2021, 卷号: 70, 页码: 13
作者:  Lv, Chengkan;  Shen, Fei;  Zhang, Zhengtao;  Xu, De;  He, Yonghao
Adobe PDF(4910Kb)  |  收藏  |  浏览/下载：318/67  |  提交时间：2021/11/03
Anomaly detection  autoencoder  background reconstruction  defect inspection  
Unsupervised Video Summarization via Relation-Aware Assignment Learning 期刊论文
IEEE TRANSACTIONS ON MULTIMEDIA, 2021, 卷号: 23, 页码: 3203-3214
作者:  Gao, Junyu;  Yang, Xiaoshan;  Zhang, Yingying;  Xu, Changsheng
Adobe PDF(3649Kb)  |  收藏  |  浏览/下载：352/69  |  提交时间：2021/11/03
Feature extraction  Training  Optimization  Semantics  Recurrent neural networks  Task analysis  Graph neural network  unsupervised learning  video summarization  
Deep convolutional self-paced clustering 期刊论文
APPLIED INTELLIGENCE, 2021, 页码: 15
作者:  Chen, Rui;  Tang, Yongqiang;  Tian, Lei;  Zhang, Caixia;  Zhang, Wensheng
Adobe PDF(2029Kb)  |  收藏  |  浏览/下载：302/61  |  提交时间：2021/11/02
Deep clustering  Convolutional autoencoder  Local structure preservation  Self-paced learning  
Variational Gridded Graph Convolution Network for Node Classification 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2021, 卷号: 8, 期号: 10, 页码: 1697-1708
作者:  Xiaobin Hong;  Tong Zhang;  Zhen Cui;  Jian Yang
Adobe PDF(2419Kb)  |  收藏  |  浏览/下载：151/44  |  提交时间：2021/09/03
Graph coarsening  gridding  node classification  random walk  variational convolution  
Semi-/Weakly-Supervised Semantic Segmentation Method and Its Application for Coastal Aquaculture Areas Based on Multi-Source Remote Sensing Images-Taking the Fujian Coastal Area (Mainly Sanduo) as an Example 期刊论文
REMOTE SENSING, 2021, 卷号: 13, 期号: 6, 页码: 21
作者:  Liang, Chenbin;  Cheng, Bo;  Xiao, Baihua;  He, Chenlinqiu;  Liu, Xunan;  Jia, Ning;  Chen, Jinfen
Adobe PDF(66625Kb)  |  收藏  |  浏览/下载：269/19  |  提交时间：2021/08/15
coastal aquaculture areas  semantic segmentation  semi-  weakly-supervised learning  GAN  conditional adversarial learning  
A Self-Supervised CNN for Particle Inspection on Optical Element 期刊论文
IEEE Transactions on Instrumentation and Measurement, 2021, 卷号: 70, 期号: 1, 页码: 1-12
作者:  Hou W(侯伟);  Tao X(陶显);  Xu D(徐德)
Adobe PDF(2721Kb)  |  收藏  |  浏览/下载：294/71  |  提交时间：2021/06/21
Inspection  Feature reuse  optical element  particle inspection  self-supervised learning  transfer learning  
A review of the application of machine learning in molecular imaging 期刊论文
Annals of Translational Medicine, 2021, 卷号: 0, 期号: 0, 页码: 0
作者:  Yin, Lin;  Cao, Zhen;  Wang, Kun;  Tian, Jie;  Yang, Xing;  Zhang, Jianhua
Adobe PDF(4435Kb)  |  收藏  |  浏览/下载：219/45  |  提交时间：2021/06/16
molecular imaging, machine learning, artificial intelligence  
CMT: Cross Mean Teacher Unsupervised Domain Adaptation for VHR Image Semantic Segmentation 期刊论文
IEEE Geoscience and Remote Sensing Letters, 2021, 卷号: 0, 期号: 0, 页码: 1-5
作者:  Liang Yan;  Bin Fan;  Shiming Xiang;  Chunhong Pan
Adobe PDF(1700Kb)  |  收藏  |  浏览/下载：204/44  |  提交时间：2021/06/15
Cross mean teacher (CMT)  self-training (ST)  semantic segmentation  unsupervised domain adaptation (UDA)  very-high-resolution (VHR) image