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Found 5 papers, 2 papers with code
Privacy-Preserving Edge Federated Learning for Intelligent Mobile-Health Systems
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.
Lightweight Inference for Forward-Forward Algorithm
The human brain performs tasks with an outstanding energy-efficiency, i. e., with approximately 20 Watts.
Verification-Friendly Deep Neural Networks
The over-approximation introduced during the formal verification process to tackle the scalability challenge often results in inconclusive analysis.
Many-to-One Knowledge Distillation of Real-Time Epileptic Seizure Detection for Low-Power Wearable Internet of Things Systems
Integrating low-power wearable Internet of Things (IoT) systems into routine health monitoring is an ongoing challenge.
Synthetic Epileptic Brain Activities Using Generative Adversarial Networks
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.
