4 citations · 6 across the 3 of their papers we have counts for
3 papers
Bridging Efficiency and Safety: Formal Verification of Neural Networks with Early Exits
Yizhak Yisrael Elboher, Avraham Raviv, Amihay Elboher +4
Ensuring the safety and efficiency of AI systems is a central goal of modern research. Formal verification provides guarantees of neural network robustness, while early exits impro…
Towards Formal Verification of Deep Neural Networks for Object Detection
Yizhak Y. Elboher, Avraham Raviv, Yael Leibovich Weiss +8
Deep neural networks (DNNs) are widely used in real-world computer vision applications, yet they remain vulnerable to errors and adversarial attacks. Formal verification offers a s…
Layer Folding: Neural Network Depth Reduction using Activation Linearization
Amir Ben Dror, Niv Zehngut, Avraham Raviv +3
Despite the increasing prevalence of deep neural networks, their applicability in resource-constrained devices is limited due to their computational load. While modern devices exhi…