Thierry BOUWMANS

Associate Professor

La Rochelle University

France

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Thierry Bouwmans is an Associate Professor at Université La Rochelle in France. His research interests include artificial intelligence applications in rare disease diagnosis, traffic forecasting using spatio-temporal graph networks, and underwater object segmentation through semi-supervised learning. Additionally, he explores methodologies for mapping acoustic heterogeneity in ecosystems and the efficiency of higher-order graph neural networks. His recent work emphasizes innovative approaches to moving object detection and change detection in thermal video scenes.

Articles (19)

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2025

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2020

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2020

Collaborators (2)

Anastasia Zakharova

La Rochelle Université

FRANCE

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Jhony Heriberto Giraldo Zuluaga

Assistant Professor

FRANCE

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Thierry BOUWMANS

Research Interests

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About

Articles (19)

Long-term spatio-temporal graph attention network for traffic forecasting

Graph-based Moving Object Segmentation for underwater videos using semi-supervised learning

AI4RDD: Artificial Intelligence and Rare Disease Diagnosis: A proposal to improve the anamnesis process

HybridGT: An Integration of Graph Transformer and LSTM for Effective Hyperspectral Band Selection

Letting ecosystems speak for themselves: An unsupervised methodology for mapping landscape acoustic heterogeneity

Higher-Order GNNs Meet Efficiency: Sparse Sobolev Graph Neural Networks

Robust and efficient FISTA-based method for moving object detection under background movements

A Multi-Scale Contrast Preserving Encoder-Decoder Architecture for Local Change Detection From Thermal Video Scenes

A Multi-scale Contrast Preserving Encoder-Decoder Architecture for Local Change Detection from Thermal Video Scenes

Reconstruction of Time-Varying Graph Signals via Sobolev Smoothness

Moving objects segmentation using generative adversarial modeling

Face Identification Using Data Augmentation Based on the Combination of DCGANs and Basic Manipulations

A Novel Algorithm Based on a Common Subspace Fusion for Visual Object Tracking

Reconstruction of Time-varying Graph Signals via Sobolev Smoothness

SemiSegSAR: A Semi-supervised Segmentation Algorithm for Ship SAR Images

Moving objects detection with a moving camera: A comprehensive review

Deep detector classifier (DeepDC) for moving objects segmentation and classification in video surveillance

Introduction to the Special Issue on Multimodal Machine Learning for Human Behavior Analysis

Background subtraction in real applications: Challenges, current models and future directions

Collaborators (2)

Anastasia Zakharova

Jhony Heriberto Giraldo Zuluaga

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