Zobrazeno 1 - 10
of 235
pro vyhledávání: '"Le Minh, Nguyen"'
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
Publikováno v:
IEEE Access, Vol 12, Pp 69488-69504 (2024)
The rapid growth of the tourism industry has spurred extensive research into tourist route planning. However, existing studies primarily focus on route planning for individual tourists, leaving a notable gap in addressing multiple tourists planning s
Externí odkaz:
https://doaj.org/article/223b91e5770e4ebfac388da4b5156afe
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
Publikováno v:
IEEE Access, Vol 11, Pp 48901-48911 (2023)
With the further development of knowledge graphs, many weighted knowledge graphs (WKGs) have been published and greatly promote various applications. However, current deterministic knowledge graph embedding algorithms cannot encode weighted knowledge
Externí odkaz:
https://doaj.org/article/43e06665ddb94bd49767f2709b291d8a
Autor:
Trong, Sinh Vu, Le, Minh Nguyen
Many approaches have been proposed to tackle the problem of Abstract Meaning Representation (AMR) parsing, helps solving various natural language processing issues recently. In our paper, we provide an overview of different methods in AMR parsing and
Externí odkaz:
http://arxiv.org/abs/1811.08078
Different word embedding models capture different aspects of linguistic properties. This inspired us to propose a model (M-MaxLSTM-CNN) for employing multiple sets of word embeddings for evaluating sentence similarity/relation. Representing each word
Externí odkaz:
http://arxiv.org/abs/1805.07882
Publikováno v:
Applied Artificial Intelligence, Vol 36, Iss 1 (2022)
Data sparsity is one of the challenges for low-resource language pairs in Neural Machine Translation (NMT). Previous works have presented different approaches for data augmentation, but they mostly require additional resources and obtain low-quality
Externí odkaz:
https://doaj.org/article/e2759d6be0ef4ca4959cff14e6be5972
Akademický článek
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Autor:
Le Minh Nguyen, Van Hoang Nguyen, Doan My Ngoc Nguyen, Minh Kha Le, Van Man Tran, My Loan Phung Le
Publikováno v:
ChemEngineering, Vol 7, Iss 2, p 33 (2023)
P-type layered oxides recently became promising candidates for Sodium-ion batteries (NIBs) for their high specific capacity and rate capability. This work elucidated the structure and electrochemical performance of the layered cathode material NaxMn0
Externí odkaz:
https://doaj.org/article/af496ee1c8784fcbaa06459e50f1e56d