R&D

The DeepRun project consists of three actions: Action 1: Design of a multi-scale image recognition tool

Bibliography on multi-scale Deep Learning image recognition tools
Development of a scientific tool specific to the conditions of the Reunionese territory
- Operation of hydrogen converters in a tropical environment (humidity and temperature)
- Diversity of Reunionese cultures and steep relief
Creation of databases with satellite images (Pléiades) and new truth maps from the DEAL REUNION / IGN
Creation of databases for hydrogen converters

Action 2: Application to the recognition of land use on a landscape scale

Detection of crop types and generation of fine maps of land use (1 per year)
Cross-referencing of maps (risks, deposits, uses) for photovoltaic decision making

Action 3: Application on a microbubble scale at the electrochemical cell scale

Creation of databases and detection of bubbles/droplets, then determination of operating regimes
Coupling of the obtained spatial distributions to models and design of a multimodal diagnostic tool