12 citations · 13 across the 5 of their papers we have counts for
6 papers
Bridging Data and Physics: A Graph Neural Network-Based Hybrid Twin Framework
M. Gorpinich, B. Moya, S. Rodriguez +6
Simulating complex unsteady physical phenomena relies on detailed mathematical models, simulated for instance by using the Finite Element Method (FEM). However, these models often…
Beyond Academic Benchmarks: Critical Analysis and Best Practices for Visual Industrial Anomaly Detection
Aimira Baitieva, Yacine Bouaouni, Alexandre Briot +3
Anomaly detection (AD) is essential for automating visual inspection in manufacturing. This field of computer vision is rapidly evolving, with increasing attention towards real-wor…
Instance-Aware Observer Network for Out-of-Distribution Object Segmentation
Victor Besnier, Andrei Bursuc, David Picard +1
Recent works on predictive uncertainty estimation have shown promising results on Out-Of-Distribution (OOD) detection for semantic segmentation. However, these methods struggle to…
Triggering Failures: Out-Of-Distribution detection by learning from local adversarial attacks in Semantic Segmentation
Victor Besnier, Andrei Bursuc, David Picard +1
In this paper, we tackle the detection of out-of-distribution (OOD) objects in semantic segmentation. By analyzing the literature, we found that current methods are either accurate…
Learning Uncertainty For Safety-Oriented Semantic Segmentation In Autonomous Driving
Victor Besnier, David Picard, Alexandre Briot
In this paper, we show how uncertainty estimation can be leveraged to enable safety critical image segmentation in autonomous driving, by triggering a fallback behavior if a target…
Leveraging Model Interpretability and Stability to increase Model Robustness
Fei Wu, Thomas Michel, Alexandre Briot
State of the art Deep Neural Networks (DNN) can now achieve above human level accuracy on image classification tasks. However their outstanding performances come along with a compl…