Low-Power Anomaly Detection and Classification System based on a Partially Binarized Autoencoder for In-Sensor Computing

Paola Vitolo, Gian Domenico Licciardo, Luigi Di Benedetto, Rosalba Liguori, Alfredo Rubino, Danilo Pau. Low-Power Anomaly Detection and Classification System based on a Partially Binarized Autoencoder for In-Sensor Computing. In 28th IEEE International Conference on Electronics, Circuits, and Systems, ICECS 2021, Dubai, United Arab Emirates, November 28 - Dec. 1, 2021. pages 1-5, IEEE, 2021. [doi]

Abstract

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