17 citations · 17 across the 3 of their papers we have counts for
4 papers
C-SWAP: Explainability-Aware Structured Pruning for Efficient Neural Networks Compression
Baptiste Bauvin, Loïc Baret, Ola Ahmad
Neural network compression has gained increasing attention in recent years, particularly in computer vision applications, where the need for model reduction is crucial for overcomi…
Causal Analysis for Robust Interpretability of Neural Networks
Ola Ahmad, Nicolas Bereux, Loïc Baret +2
Interpreting the inner function of neural networks is crucial for the trustworthy development and deployment of these black-box models. Prior interpretability methods focus on corr…
FisheyeHDK: Hyperbolic Deformable Kernel Learning for Ultra-Wide Field-of-View Image Recognition
Ola Ahmad, Freddy Lecue
Conventional convolution neural networks (CNNs) trained on narrow Field-of-View (FoV) images are the state-of-the-art approaches for object recognition tasks. Some methods proposed…
Adaptable Deformable Convolutions for Semantic Segmentation of Fisheye Images in Autonomous Driving Systems
Clément Playout, Ola Ahmad, Freddy Lecue +1
Advanced Driver-Assistance Systems rely heavily on perception tasks such as semantic segmentation where images are captured from large field of view (FoV) cameras. State-of-the-art…