1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.LG2020★ 1 cited
Addressing Neural Network Robustness with Mixup and Targeted Labeling Adversarial Training
Alfred Laugros, Alice Caplier, Matthieu Ospici
Despite their performance, Artificial Neural Networks are not reliable enough for most of industrial applications. They are sensitive to noises, rotations, blurs and adversarial ex…
cs.LG2019
Are Adversarial Robustness and Common Perturbation Robustness Independent Attributes ?
Alfred Laugros, Alice Caplier, Matthieu Ospici
Neural Networks have been shown to be sensitive to common perturbations such as blur, Gaussian noise, rotations, etc. They are also vulnerable to some artificial malicious corrupti…
cs.CV2019
ADS-ME: Anomaly Detection System for Micro-expression Spotting
Dawood Al Chanti, Alice Caplier
Micro-expressions (MEs) are infrequent and uncontrollable facial events that can highlight emotional deception and appear in a high-stakes environment. This paper propose an algori…