Zobrazeno 1 - 10
of 43
pro vyhledávání: '"Zhenghan Chen"'
Publikováno v:
IEEE Access, Vol 12, Pp 140734-140747 (2024)
Remote sensing image classification is pivotal in applications ranging from environmental monitoring to urban planning. However, the scarcity of labeled data in target domains often impedes the generalization of models trained on source domains. To a
Externí odkaz:
https://doaj.org/article/0def662a79ee4d3f8d7c081649dde97e
Publikováno v:
IEEE Access, Vol 12, Pp 98254-98269 (2024)
Lane detection is fundamental to autonomous driving, yet remains challenging in complex environments with occlusions, ambiguous markings, and varied lighting. We introduce the Global Semantic Enhancement Network (GSENet), a groundbreaking framework t
Externí odkaz:
https://doaj.org/article/0302070dce4f4ffaaa28b12959300147
Autor:
Yin Wang, Zhenghan Chen
Publikováno v:
IEEE Access, Vol 11, Pp 6513-6523 (2023)
Grammatical error correction aims to detect and correct grammatical errors with all types of mistaken, disordered, missing, and redundant characters. However, most existing methods focus more on detecting errors than correcting them. This paper propo
Externí odkaz:
https://doaj.org/article/0bf4a692d046428e9e0c17786e75c551
Publikováno v:
Sensors, Vol 22, Iss 21, p 8450 (2022)
Emotional tracking on time-varying virtual space communication aims to identify sentiments and opinions expressed in a piece of user-generated content. However, the existing research mainly focuses on the user’s single post, despite the fact that s
Externí odkaz:
https://doaj.org/article/bf507749180d454a9f9f68ee32cc6053
Publikováno v:
Complexity, Vol 2021 (2021)
In recent years, deep neural networks have achieved great success in many fields, such as computer vision and natural language processing. Traditional image recommendation algorithms use text-based recommendation methods. The process of displaying im
Externí odkaz:
https://doaj.org/article/377f97382545486686ef19ef3d987551
Autor:
Ye Wang, Yingmin Zhou, Mengzhu Wang, Zhenghan Chen, Zhiping Cai, Junyang Chen, Victor C. M. Leung
Publikováno v:
IEEE Transactions on Computational Social Systems. :1-10
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c6f5f5a9dca2c725709276698388c829
https://doi.org/10.1109/tcss.2023.3252723
https://doi.org/10.1109/tcss.2023.3252723
Autor:
Changzeng Fu, Zhenghan Chen, Jiaqi Shi, Bowen Wu, Chaoran Liu, Carlos Toshinori Ishi, Hiroshi Ishiguro
Publikováno v:
ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b44a06a16c5986c8adc7b8d98bf007d7
https://doi.org/10.1109/icassp49357.2023.10096805
https://doi.org/10.1109/icassp49357.2023.10096805
Publikováno v:
Journal of Testing & Evaluation; Nov2023, Vol. 51 Issue 6, p1-21, 21p
International Classification of Diseases (ICD) coding has been considered as a multi-label prediction problem, requiring the assignment of one or more codes to a detailed discharge summary. Existing automatic ICD coding algorithms struggle to effecti
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::71ebbb6ff29e863e3f15f3e3b45e8d12
https://doi.org/10.21203/rs.3.rs-2613478/v1
https://doi.org/10.21203/rs.3.rs-2613478/v1
