معرفی
Max Mignotte is a Full Professor at the Department of Computer Science and Operations Research, Faculty of Arts and Sciences, Université de Montréal. He leads research in Image Processing, Remote Sensing, and Bayesian Inference, focusing on applications in medical imaging, computer vision, and data fusion. His work includes developing advanced algorithms for saliency estimation, multimodal change detection, and 3D reconstruction.
Research Interests: Image processing techniques for medical diagnostics, remote sensing analysis, and machine learning-driven solutions for visual attention and segmentation. His methodologies often integrate Bayesian models and fusion strategies to address complex problems in computer vision and biomedical applications.
Key Projects:
- Leading the Multi-Dimensional Scaling Maps for Saliency Estimation initiative.
- Developing Bayesian fusion models for remote sensing applications.
- Advancing 3D biplanar reconstruction of human limbs using statistical models.
Grants & Teams: Principal investigator on CRSNG-funded projects, including New unsupervised Bayesian and energy-based models (2022–2028) and Bayesian fusion models (2016–2023). Collaborates with the Laboratoire de traitement d’images and interdisciplinary teams in biomedical research.
