The project, funded by Fonds de recherche du Québec – Nature et technologies (FRQNT), in partnership with the Ministère de l'Énergie et Ressources naturelles (MERN), under its second sustainable mining partnership research program, will analyze all airborne image data to predict the nature of the subsoil. The algorithms generated can be used as guides to target mineral exploration sites. This new approach to artificial intelligence aims to train parallel neural networks, each processing one type of variable, such as aeromagnetic or electromagnetic data. When processing is complete, a system will combine each network's predictions to generate a final prediction. Professor Gloaguen's team is working with experts in artificial intelligence applied to mining for this network development project, the first phase of which is already underway.