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]

@inproceedings{VitoloLBLRP21,
  title = {Low-Power Anomaly Detection and Classification System based on a Partially Binarized Autoencoder for In-Sensor Computing},
  author = {Paola Vitolo and Gian Domenico Licciardo and Luigi Di Benedetto and Rosalba Liguori and Alfredo Rubino and Danilo Pau},
  year = {2021},
  doi = {10.1109/ICECS53924.2021.9665479},
  url = {https://doi.org/10.1109/ICECS53924.2021.9665479},
  researchr = {https://researchr.org/publication/VitoloLBLRP21},
  cites = {0},
  citedby = {0},
  pages = {1-5},
  booktitle = {28th IEEE International Conference on Electronics, Circuits, and Systems, ICECS 2021, Dubai, United Arab Emirates, November 28 - Dec. 1, 2021},
  publisher = {IEEE},
  isbn = {978-1-7281-8281-0},
}