Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Hong N. Dao"'
Publikováno v:
IEEE Access, Vol 12, Pp 75496-75507 (2024)
Medical image data often face the problem of data scarcity and costly annotation processes. To overcome this, our study introduces a novel transfer learning method for medical image classification. We present a multimodal learning framework that inco
Externí odkaz:
https://doaj.org/article/0ee381395c18444e8763b472189e94f2
Autor:
Hong N. Dao, Penugonda Ravikumar, Palla Likhitha, Uday Kiran Rage, Yutaka Watanobe, Incheon Paik
Publikováno v:
IEEE Access, Vol 11, Pp 12504-12524 (2023)
Stable periodic-frequent itemset mining is essential in big data analytics with many real-world applications. It involves extracting all itemsets exhibiting stable periodic behaviors in a temporal database. Most previous studies focused on finding th
Externí odkaz:
https://doaj.org/article/503677ea9ef34b48a0738b0b8f6940ac
Publikováno v:
2022 IEEE International Conference on Consumer Electronics-Asia (ICCE-Asia).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a7ae81a6ce0f6ced232641dbcec7f0f8
https://doi.org/10.1109/icce-asia57006.2022.9954669
https://doi.org/10.1109/icce-asia57006.2022.9954669
Autor:
Hong N. Dao, Penugonda Ravikumar, P. Likitha, Bathala Venus Vikranth Raj, R. Uday Kiran, Yutaka Watanobe, Incheon Paik
Publikováno v:
Advances and Trends in Artificial Intelligence. Theory and Practices in Artificial Intelligence ISBN: 9783031085291
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bb65718e4440a3998eee2c83d877a5a5
https://doi.org/10.1007/978-3-031-08530-7_70
https://doi.org/10.1007/978-3-031-08530-7_70
