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of 483
pro vyhledávání: '"Tuấn Anh Nguyễn"'
Measuring the confidence of AI models is critical for safely deploying AI in real-world industrial systems. One important application of confidence measurement is information extraction from scanned documents. However, there exists no solution to pro
Externí odkaz:
http://arxiv.org/abs/2206.02628
Publikováno v:
In Infrared Physics and Technology September 2024 141
Autor:
Thong, Dang Quang, Le Minh Quoc, Ho, Dat, Tran Quang, Hai, Nguyen Viet, Nguyen, Doan Thuy, Tuan Anh, Nguyen Vu, Vuong, Nguyen Lam, Bac, Nguyen Hoang, Long, Vo Duy
Publikováno v:
In Surgery June 2024 175(6):1524-1532
Publikováno v:
2020 25th International Conference on Pattern Recognition (ICPR)
Form understanding is a challenging problem which aims to recognize semantic entities from the input document and their hierarchical relations. Previous approaches face significant difficulty dealing with the complexity of the task, thus treat these
Externí odkaz:
http://arxiv.org/abs/2106.00980
Publikováno v:
30th British Machine Vision Conference (BMVC) 2019
Information extraction from document images has received a lot of attention recently, due to the need for digitizing a large volume of unstructured documents such as invoices, receipts, bank transfers, etc. In this paper, we propose a novel deep lear
Externí odkaz:
http://arxiv.org/abs/2106.00952
Akademický článek
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This paper proposes Medley of Sub-Attention Networks (MoSAN), a new novel neural architecture for the group recommendation task. Group-level recommendation is known to be a challenging task, in which intricate group dynamics have to be considered. As
Externí odkaz:
http://arxiv.org/abs/1804.04327
Publikováno v:
In Finance Research Letters June 2022 47 Part B
Akademický článek
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We describe the 1st place winning approach for the CIKM Cup 2016 Challenge. In this paper, we provide an approach to reasonably identify same users across multiple devices based on browsing logs. Our approach regards a candidate ranking problem as pa
Externí odkaz:
http://arxiv.org/abs/1610.07119