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pro vyhledávání: '"Anzaku, Esla Timothy"'
Autor:
Anzaku, Esla Timothy, Hong, Hyesoo, Park, Jin-Woo, Yang, Wonjun, Kim, Kangmin, Won, JongBum, Herath, Deshika Vinoshani Kumari, Van Messem, Arnout, De Neve, Wesley
Large-scale datasets for single-label multi-class classification, such as \emph{ImageNet-1k}, have been instrumental in advancing deep learning and computer vision. However, a critical and often understudied aspect is the comprehensive quality assess
Externí odkaz:
http://arxiv.org/abs/2401.17736
Autor:
Ozbulak, Utku, Lee, Hyun Jung, Boga, Beril, Anzaku, Esla Timothy, Park, Homin, Van Messem, Arnout, De Neve, Wesley, Vankerschaver, Joris
Publikováno v:
Transactions on Machine Learning Research, 2023
Although supervised learning has been highly successful in improving the state-of-the-art in the domain of image-based computer vision in the past, the margin of improvement has diminished significantly in recent years, indicating that a plateau is i
Externí odkaz:
http://arxiv.org/abs/2305.13689
Deep Neural Network (DNN) models are increasingly evaluated using new replication test datasets, which have been carefully created to be similar to older and popular benchmark datasets. However, running counter to expectations, DNN classification mod
Externí odkaz:
http://arxiv.org/abs/2209.01848
Although the adoption rate of deep neural networks (DNNs) has tremendously increased in recent years, a solution for their vulnerability against adversarial examples has not yet been found. As a result, substantial research efforts are dedicated to f
Externí odkaz:
http://arxiv.org/abs/2106.07141
Akademický článek
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Akademický článek
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Publikováno v:
Digital Watermarking (9783642184048); 2011, p239-250, 12p
