Zobrazeno 1 - 3
of 3
pro vyhledávání: '"Yassine Jaoudi"'
Publikováno v:
IGSC (Workshops)
Across industry, there is an increasing availability of streaming, time-varying data, where it is important to detect anomalous behavior. These data are found in an enormous number of sensor-based applications, in cybersecurity (where anomalous behav
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6dcc4f187e18dbe3a346b527ca862288
https://doi.org/10.1109/igsc51522.2020.9291232
https://doi.org/10.1109/igsc51522.2020.9291232
Autor:
Yassine Jaoudi, B. Rasitha Fernando, Md. Shahanur Alam, Tarek M. Taha, Guru Subramanyam, Raqibul Hasan, Chris Yakopcic
Publikováno v:
ICONS
Custom low power hardware for real-time network security and anomaly detection are in great demand, as these would allow for efficient security in battery-powered network devices. This paper presents a memristor based system for real-time intrusion d
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::740c2d4fde9782f4e1b18077847fce55
https://doi.org/10.1145/3354265.3354267
https://doi.org/10.1145/3354265.3354267
Autor:
Hsinyu Tsai, Irem Boybat, Carmelo di Nolfo, Geoffrey W. Burr, Robert M. Shelby, Nathan C. P. Farinha, Severin Sidler, Pritish Narayanan, Martina Bodini, Yassine Jaoudi, Christina Cheng, Massimo Giordano, Benjamin Killeen, Stefano Ambrogio
Publikováno v:
Nature. 558(7708)
Neural-network training can be slow and energy intensive, owing to the need to transfer the weight data for the network between conventional digital memory chips and processor chips. Analogue non-volatile memory can accelerate the neural-network trai
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::55e9b182c6d079cc24b63f25a8367da2
https://pubmed.ncbi.nlm.nih.gov/29872204
https://pubmed.ncbi.nlm.nih.gov/29872204