方超伟
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现为西安电子科技大学人工智能学院副教授,智能感知与图像理解教育部重点实验室成员。2019年获得香港大学计算机系博士学位,2013年获得西安交通大学自动化系学士学位,2013-2015年期间于西安交通大学人工智能与机器人研究所读研究生。主要研究兴趣包括计算机视觉、图像视频处理、医学影像分析等。在人工智能、计算机视觉、机器学习、医学图像计算等领域的顶级期刊/会议发表多篇论文。更多信息请关注个人主页:https://chaoweifang.github.io/。
正在招聘硕士生和本科实习生,如有兴趣,请将简历和成绩单发送至邮箱:chaoweifang[AT]outlook.com
代表性论文:
1. Guanbin Li , Zhuohua Chen , Mingzhi Mao , Liang Lin , Chaowei Fang † . Uncertainty-aware Active Domain Adaptive Salient Object Detection. TIP, 2024. (一区)
2. Chaowei Fang , Lechao Cheng , Yining Mao , Dingwen Zhang , Yixiang Fang , Guanbin Li , Huiyan Qi , Licheng Jiao . Separating Noisy Samples from Tail Classes for Long-Tailed Image Classification with Label Noise. TNNLS, 2023. (一区)
3. Kuo Wang, Yuxiang Nie, Chaowei Fang, Chengzhi Han, Xuewen Wu, Xiaohui Wang, Liang Lin, Fan Zhou, Guanbin Li. "Double-Check Soft Teacher for Semi-Supervised Object Detection." In IJCAI, 2022. (CCF A)
4. Chaowei Fang*, Liang Wang*, Dingwen Zhang, Jun Xu, Yixuan Yuan, Junwei Han. "Incremental Cross-view Mutual Distillation for Self-supervised Medical CT Synthesis." In CVPR, 2022. (CCF A)
5. Junkai Huang*, Chaowei Fang*, Weikai Chen, Zhenhua Chai, Xiaolin Wei, Pengxu Wei, Liang Lin, Guanbin Li. "Trash to Treasure: Harvesting OOD Data with Cross-Modal Matching for Open-Set Semi-Supervised Learning." In ICCV, 2021. (CCF A)
6. Gangming Zhao*, Chaowei Fang*, Guanbin Li, Licheng Jiao, Yizhou Yu. "Contralaterally Enhanced Networks for Thoracic Disease Detection." IEEE Transactions on Medical Imaging, 2021.(一区)
7. Zhu, Feida, Chaowei Fang† , Kai-Kuang Ma. "PNEN: Pyramid Non-Local Enhanced Networks." In IEEE Transactions on Image Processing (TIP), 2020. (一区)
8. Chaowei Fang, Guanbin Li, Xiaoguang Han, Yizhou Yu. "Self-Enhanced Convolutional Network for Facial Video Hallucination." In TIP, 2019. (一区)
9. Chaowei Fang, Guanbin Li, Chengwei Pan, Yiming Li, Yizhou Yu. "Globally Guided Progressive Fusion Network for 3D Pancreas Segmentation." In MICCAI, 2019.
10. Chaowei Fang, Zicheng Liao, Yizhou Yu. "Piecewise Flat Embedding for Image Segmentation." IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2018. (一区)
底层图像处理:图像超分、图像修复、图像生成等
鲁棒机器学习:面向标注数量少、质量差、噪声多、适应性差等场景开发机器学习算法
医学图像计算:面向MRI、X光片等开发图像处理和辅助诊断模型