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pro vyhledávání: '"Zeeshan, Muhammad Osama"'
Autor:
Aslam, Muhammad Haseeb, Zeeshan, Muhammad Osama, Belharbi, Soufiane, Pedersoli, Marco, Koerich, Alessandro, Bacon, Simon, Granger, Eric
Deep learning models for multimodal expression recognition have reached remarkable performance in controlled laboratory environments because of their ability to learn complementary and redundant semantic information. However, these models struggle in
Externí odkaz:
http://arxiv.org/abs/2401.15489
Autor:
Zeeshan, Muhammad Osama, Aslam, Muhammad Haseeb, Belharbi, Soufiane, Koerich, Alessandro Lameiras, Pedersoli, Marco, Bacon, Simon, Granger, Eric
Adapting a deep learning model to a specific target individual is a challenging facial expression recognition (FER) task that may be achieved using unsupervised domain adaptation (UDA) methods. Although several UDA methods have been proposed to adapt
Externí odkaz:
http://arxiv.org/abs/2312.05632
This four-volume set of LNCS 12821, LNCS 12822, LNCS 12823 and LNCS 12824, constitutes the refereed proceedings of the 16th International Conference on Document Analysis and Recognition, ICDAR 2021, held in Lausanne, Switzerland in September 2021. Th