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pro vyhledávání: '"HOANG, Tuan"'
Unsupervised domain adaptation (UDA) has become increasingly prevalent in scene text recognition (STR), especially where training and testing data reside in different domains. The efficacy of existing UDA approaches tends to degrade when there is a l
Externí odkaz:
http://arxiv.org/abs/2410.09913
Autor:
Oh, Taekkyung, Bae, Sangwook, Ahn, Junho, Lee, Yonghwa, Hoang, Tuan Dinh, Kang, Min Suk, Tippenhauer, Nils Ole, Kim, Yongdae
In cellular networks, authorities may need to physically locate user devices to track criminals or illegal equipment. This process involves authorized agents tracing devices by monitoring uplink signals with cellular operator assistance. However, tra
Externí odkaz:
http://arxiv.org/abs/2403.14963
In this paper, we tackle the problem of computing a sequence of rankings with the guarantee of the Pareto-optimal balance between (1) maximizing the utility of the consumers and (2) minimizing unfairness between producers of the items. Such a multi-o
Externí odkaz:
http://arxiv.org/abs/2402.14305
Recent data-privacy laws have sparked interest in machine unlearning, which involves removing the effect of specific training samples from a learnt model as if they were never present in the original training dataset. The challenge of machine unlearn
Externí odkaz:
http://arxiv.org/abs/2312.04095
Publikováno v:
Acta Crystallographica Section E: Crystallographic Communications, Vol 80, Iss 7, Pp 795-799 (2024)
A new quinoline derivative, namely, 6-(diethylamino)-4-phenyl-2-(pyridin-2-yl)quinoline, C24H23N3 (QP), and its MnII complex aqua-1κO-di-μ-chlorido-1:2κ4Cl:Cl-dichlorido-1κCl,2κCl-bis[6-(diethylamino)-4-phenyl-2-(pyridin-2-yl)quinoline]-1κ2N1,N
Externí odkaz:
https://doaj.org/article/dbf197eaaddb4aa9a76303a254db39ea
Knowledge distillation which learns a lightweight student model by distilling knowledge from a cumbersome teacher model is an attractive approach for learning compact deep neural networks (DNNs). Recent works further improve student network performan
Externí odkaz:
http://arxiv.org/abs/2210.16103
Autor:
Nguyen, Thi Thu Ha, Vu, Duc Quang, Doan, Ngoc Phu, Chi, Huynh Thi Khanh, Li, Peixin, Binh, Doan Van, An, Yimeng, Dung, Pham Tuan, Hoang, Tuan A., Son, Mai Thai
Publikováno v:
In Science of the Total Environment 10 December 2024 955
Autor:
Hoang, Van-Hiep, Nguyen, Minh-Ky, Hoang, Tuan-Dung, Ha, Minh Cuong, Huyen, Nguyen Thi Thanh, Bui, Vu Khac Hoang, Pham, Minh-Thuan, Nguyen, Cong-Manh, Chang, S. Woong, Nguyen, D. Duc
Publikováno v:
In Science of the Total Environment 10 November 2024 950
Autor:
Hien, Nguyen, Khanh, Nguyen Nhat, Pham, Van Thong, Dung, Tran Ngoc, Duong, Hoang Tuan, Giang, Nguyen Hoang, Anh, Nguyen Duc, Van Meervelt, Luc, Hai, Le Thi Hong
Publikováno v:
In Journal of Molecular Structure 15 February 2025 1322 Part 3
In this paper, we adopt the maximizing mutual information (MI) approach to tackle the problem of unsupervised learning of binary hash codes for efficient cross-modal retrieval. We proposed a novel method, dubbed Cross-Modal Info-Max Hashing (CMIMH).
Externí odkaz:
http://arxiv.org/abs/2112.06489