Zobrazeno 1 - 3
of 3
pro vyhledávání: '"Weikun Kong"'
Autor:
Yao Wang, Xin Liu, Weikun Kong, Hai-Tao Yu, Teeradaj Racharak, Kyoung-Sook Kim, Le Minh Nguyen
Publikováno v:
IEEE Access, Vol 12, Pp 103313-103328 (2024)
Named Entity Recognition and Relation Extraction are two crucial and challenging subtasks in Information Extraction. Despite the successes achieved by the traditional approaches, fundamental research questions remain open. First, most recent studies
Externí odkaz:
https://doaj.org/article/8ee240f378ef44d4a70757e446001dfb
Autor:
Guanqun Sun, Han Shu, Feihe Shao, Teeradaj Racharak, Weikun Kong, Yizhi Pan, Jingjing Dong, Shuang Wang, Le-Minh Nguyen, Junyi Xin
Publikováno v:
IEEE Access, Vol 12, Pp 33687-33704 (2024)
Advances in deep learning have revolutionized medical image segmentation, facilitating the precise delineation of complex anatomical structures. The scarcity of annotated training samples remains a significant bottleneck. To tackle the data limitatio
Externí odkaz:
https://doaj.org/article/47c0db40fdc74c97a7d29beaa0dabe42
Autor:
Guanqun Sun, Yizhi Pan, Weikun Kong, Zichang Xu, Jianhua Ma, Teeradaj Racharak, Le-Minh Nguyen, Junyi Xin
Publikováno v:
Frontiers in Bioengineering and Biotechnology, Vol 12 (2024)
Accurate medical image segmentation is critical for disease quantification and treatment evaluation. While traditional U-Net architectures and their transformer-integrated variants excel in automated segmentation tasks. Existing models also struggle
Externí odkaz:
https://doaj.org/article/07ca052e6e4d4b1eb0f9aa4e0d0765f2