Biologically Inspired Variational Auto-Encoders for Adversarial Robustness
In: The International Conference on Deep Learning, Big Data and Blockchain (DBB 2022), Jg. 541 (2023), S. 79-93
Online
E-Book
Zugriff:
Titel: |
Biologically Inspired Variational Auto-Encoders for Adversarial Robustness
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Autor/in / Beteiligte Person: | Talafha, Sameerah ; Rekabdar, Banafsheh ; Mousas, Christos ; Ekenna, Chinwe ; Kacprzyk, Janusz, Series Editor ; Gomide, Fernando, Advisory Editor ; Kaynak, Okyay, Advisory Editor ; Liu, Derong, Advisory Editor ; Pedrycz, Witold, Advisory Editor ; Polycarpou, Marios M., Advisory Editor ; Rudas, Imre J., Advisory Editor ; Wang, Jun, Advisory Editor ; Awan, Irfan [Ed.] ; Younas, Muhammad [Ed.] ; Bentahar, Jamal [Ed.] ; Benbernou, Salima [Ed.] |
Zeitschrift: | The International Conference on Deep Learning, Big Data and Blockchain (DBB 2022), Jg. 541 (2023), S. 79-93 |
Veröffentlichung: | 2023 |
Medientyp: | E-Book |
ISBN: | 978-3-031-16034-9 (print) ; 978-3-031-16035-6 (print) |
DOI: | 10.1007/978-3-031-16035-6_7 |
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