1 code implementation • 9 May 2024 • Amin Aminifar, Matin Shokri, Amir Aminifar
However, enabling learning from distributed data over such edge Internet of Things (IoT) systems (e. g., mobile-health and wearable technologies, involving sensitive personal/medical data) in a privacy-preserving fashion presents a major challenge mainly due to their stringent resource constraints, i. e., limited computing capacity, communication bandwidth, memory storage, and battery lifetime.
no code implementations • 8 Apr 2024 • Amin Aminifar, Baichuan Huang, Azra Abtahi, Amir Aminifar
The human brain performs tasks with an outstanding energy-efficiency, i. e., with approximately 20 Watts.
no code implementations • 15 Dec 2023 • Anahita Baninajjar, Ahmed Rezine, Amir Aminifar
The over-approximation introduced during the formal verification process to tackle the scalability challenge often results in inconclusive analysis.
no code implementations • 20 Jul 2022 • Saleh Baghersalimi. Alireza Amirshahi, Farnaz Forooghifar, Tomas Teijeiro, Amir Aminifar, David Atienza
Integrating low-power wearable Internet of Things (IoT) systems into routine health monitoring is an ongoing challenge.
1 code implementation • 22 Jul 2019 • Damian Pascual, Amir Aminifar, David Atienza, Philippe Ryvlin, Roger Wattenhofer
In this work, we generate synthetic seizure-like brain electrical activities, i. e., EEG signals, that can be used to train seizure detection algorithms, alleviating the need for recorded data.