Multi-Stream Cellular Test-Time Adaptation of Real-Time Models Evolving in Dynamic Environments

2 code implementations • 27 Apr 2024 • Benoît Gérin, Anaïs Halin, Anthony Cioppa, Maxim Henry, Bernard Ghanem, Benoît Macq, Christophe De Vleeschouwer, Marc Van Droogenbroeck

In the era of the Internet of Things (IoT), objects connect through a dynamic network, empowered by technologies like 5G, enabling real-time data sharing.

Autonomous Vehicles Benchmarking +2

Online Distillation with Continual Learning for Cyclic Domain Shifts

1 code implementation • 3 Apr 2023 • Joachim Houyon, Anthony Cioppa, Yasir Ghunaim, Motasem Alfarra, Anaïs Halin, Maxim Henry, Bernard Ghanem, Marc Van Droogenbroeck

In this paper, we propose a solution to this issue by leveraging the power of continual learning methods to reduce the impact of domain shifts.

Autonomous Driving Continual Learning

Mixture Domain Adaptation to Improve Semantic Segmentation in Real-World Surveillance

1 code implementation • 18 Nov 2022 • Sébastien Piérard, Anthony Cioppa, Anaïs Halin, Renaud Vandeghen, Maxime Zanella, Benoît Macq, Saïd Mahmoudi, Marc Van Droogenbroeck

In this paper, we define a probabilistic framework and present a formal proof of an algorithm for the unsupervised many-to-infinity domain adaptation of posteriors.

Bayesian Inference Domain Adaptation +1

Survey and synthesis of state of the art in driver monitoring

no code implementations • 1 Oct 2021 • Anaïs Halin, Jacques G. Verly, Marc Van Droogenbroeck

Road-vehicle accidents are mostly due to human errors, and many such accidents could be avoided by continuously monitoring the driver.