4 citations · 6 across the 5 of their papers we have counts for
3 papers · 1 filter
3D Labeling Tool
John Rachwan, Charbel Zalaket
Training and testing supervised object detection models require a large collection of images with ground truth labels. Labels define object classes in the image, as well as their l…
On the Robustness and Anomaly Detection of Sparse Neural Networks
Morgane Ayle, Bertrand Charpentier, John Rachwan +3
The robustness and anomaly detection capability of neural networks are crucial topics for their safe adoption in the real-world. Moreover, the over-parameterization of recent netwo…
Winning the Lottery Ahead of Time: Efficient Early Network Pruning
John Rachwan, Daniel Zügner, Bertrand Charpentier +3
Pruning, the task of sparsifying deep neural networks, received increasing attention recently. Although state-of-the-art pruning methods extract highly sparse models, they neglect…