The team's research focuses on the development of computer vision, image analysis, and optimization methods, which are largely applied in different fields as: biomedical medical engineering and intelligents transportation systems. The work of the team is divided into two main topics: (i) computer vision and image processing and (ii) metaheuristics and stochastic optimization.

It is remarkable how effortlessly our brains can interpret visual stimuli and extract meaningful information from them. Our ultimate objective is to replicate this ability by developing technology that can effectively analyze images and provide insights about the surrounding environment.
Our research is concentrated on a particular area, namely, video sequences analysis for rare events detection (anomaly detection, objects tracking, etc.). Additionally, we are involved in diverse fields, such as multi-camera surveillance, computer-assisted engineering, and medical image processing.

Moreover, the team's work in metaheuristics and stochastic optimization focuses mainly on the development of optimization methods applied mostly to computer vision and image processing. The team is working more specifically on the development of new approaches to solve large scale and dynamic optimization problems, encountered in the case of meta-learning, dynamic optimization and the optimization of hyper-parameters in deep learning. The targeted applications concern medical imaging, and intelligent transportation systems.

In addition to our research activities, we offer teaching to both undergraduate and graduate students, as well as transfer technology to established and start-up companies.

SIMO conducts research in close collaboration with numerous clinical and industrial partners.