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pro vyhledávání: '"Kalkhoran, Seyyed Amirhossein Ameli"'
Autor:
Kalkhoran, Seyyed Amirhossein Ameli, Letafati, Mehdi, Erdemir, Ecenaz, Khalaj, Babak Hossein, Behroozi, Hamid, Gündüz, Deniz
In this paper, a generalization of deep learning-aided joint source channel coding (Deep-JSCC) approach to secure communications is studied. We propose an end-to-end (E2E) learning-based approach for secure communication against multiple eavesdropper
Externí odkaz:
http://arxiv.org/abs/2308.02892
Autor:
Kalkhoran, Seyyed AmirHossein Ameli, Banayeeanzade, Mohammadamin, Samiei, Mahdi, Baghshah, Mahdieh Soleymani
The existing continual learning methods are mainly focused on fully-supervised scenarios and are still not able to take advantage of unlabeled data available in the environment. Some recent works tried to investigate semi-supervised continual learnin
Externí odkaz:
http://arxiv.org/abs/2301.04506