8 citations · 19 across the 19 of their papers we have counts for
5 papers · 1 filter
Bespoke Co-processor for Energy-Efficient Health Monitoring on RISC-V-based Flexible Wearables
Theofanis Vergos, Polykarpos Vergos, Mehdi B. Tahoori +1
Flexible electronics offer unique advantages for conformable, lightweight, and disposable healthcare wearables. However, their limited gate count, large feature sizes, and high sta…
Exploration of Low-Power Flexible Stress Monitoring Classifiers for Conformal Wearables
Florentia Afentaki, Sri Sai Rakesh Nakkilla, Konstantinos Balaskas +6
Conventional stress monitoring relies on episodic, symptom-focused interventions, missing the need for continuous, accessible, and cost-efficient solutions. State-of-the-art approa…
Few-Shot Testing: Estimating Uncertainty of Memristive Deep Neural Networks Using One Bayesian Test Vector
Soyed Tuhin Ahmed, Mehdi Tahoori
The performance of deep learning algorithms such as neural networks (NNs) has increased tremendously recently, and they can achieve state-of-the-art performance in many domains. Ho…
Tiny Deep Ensemble: Uncertainty Estimation in Edge AI Accelerators via Ensembling Normalization Layers with Shared Weights
Soyed Tuhin Ahmed, Michael Hefenbrock, Mehdi B. Tahoori
The applications of artificial intelligence (AI) are rapidly evolving, and they are also commonly used in safety-critical domains, such as autonomous driving and medical diagnosis,…
Enhancing Reliability of Neural Networks at the Edge: Inverted Normalization with Stochastic Affine Transformations
Soyed Tuhin Ahmed, Kamal Danouchi, Guillaume Prenat +2
Bayesian Neural Networks (BayNNs) naturally provide uncertainty in their predictions, making them a suitable choice in safety-critical applications. Additionally, their realization…