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pro vyhledávání: '"Robbiano, Luca"'
Neural Networks design is a complex and often daunting task, particularly for resource-constrained scenarios typical of mobile-sized models. Neural Architecture Search is a promising approach to automate this process, but existing competitive methods
Externí odkaz:
http://arxiv.org/abs/2310.04179
Publikováno v:
2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)
In the last decade, most research in Machine Learning contributed to the improvement of existing models, with the aim of increasing the performance of neural networks for the solution of a variety of different tasks. However, such advancements often
Externí odkaz:
http://arxiv.org/abs/2207.05135
Autor:
Robbiano, Luca, Rahman, Muhammad Rameez Ur, Galasso, Fabio, Caputo, Barbara, Carlucci, Fabio Maria
Unsupervised Domain Adaptation (UDA) is a key issue in visual recognition, as it allows to bridge different visual domains enabling robust performances in the real world. To date, all proposed approaches rely on human expertise to manually adapt a gi
Externí odkaz:
http://arxiv.org/abs/2102.06679
Autor:
Loghmani, Mohammad Reza, Robbiano, Luca, Planamente, Mirco, Park, Kiru, Caputo, Barbara, Vincze, Markus
Unsupervised Domain Adaptation (DA) exploits the supervision of a label-rich source dataset to make predictions on an unlabeled target dataset by aligning the two data distributions. In robotics, DA is used to take advantage of automatically generate
Externí odkaz:
http://arxiv.org/abs/2004.10016
In the last decade, most research in Machine Learning contributed to the improvement of existing models, with the aim of increasing the performance of neural networks for the solution of a variety of different tasks. However, such advancements often
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d72bca99e24579ed2b30975d76d355fc
http://hdl.handle.net/11583/2972504
http://hdl.handle.net/11583/2972504