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个人简介
My research interests lie in deep learning and computer vision. My most recent projects are deep clustering (DC) and unsupervised semantic segmentation (USS). In our DC project, we apply contrastive learning among the neighbor of each data sample to contract similar samples and expand dissimilar samples simultaneously to generate compact clusters. USS utilizes clustering first to generate class-level pseudo labels, which are further used as ground truth image labels to train a classification network (e.g., ResNet) to generate pixel-wise pseudo segmentation labels. These pixel-wise pseudo labels can be used as labels in a segmentation framework to implement semantic segmentation tasks.
When I was a Master student, I did research with lab mates on mobile computing (i.e., identifying human activities with sensing signals sent and received from mobile sensors using deep learning) and have publications. In the early stage of my Ph.D., I also experienced research in medical imaging (i.e., Alzheimer's disease classification on brain connectivities) and have two first-author publications in this field.
研究兴趣
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ELECTRONICSno. 5 (2023)
European Conference on Artificial Intelligence (ECAI)pp.3313-3320, (2022)
user-61447a76e55422cecdaf7d19(2021)
arXiv (Cornell University) (2021)
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Hongfei Xue, Wenjun Jiang,Chenglin Miao,Ye Yuan, Fenglong Ma,Xin Ma,Yijiang Wang,Shuochao Yao, Wenyao Xu,Aidong Zhang,Lu Su
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