Louis REBERGA

This project using Siamese Neural Networks (SNN) for seismic data analysis in geophysics. The goal is to develop an algorithm that identifies and matches similar seismic features, assisting geoscientists in interpreting subsurface geological structures.

Deep Learning solution for multi-layer seismic data segmentation using Meta's SAM, trained on a dataset of 9,000 volumes for improved subsurface mapping.

Harness the power of machine learning to forecast rice and wheat crop yields per acre in India, aiming to empower smallholder farmers, combat poverty and malnutrition, utilizing data from Digital Green surveys to revolutionize agriculture and promote sustainable practices in the face of climate change for enhanced global food security. Github : https://github.com/association-rosia/crop-yield-estimate

Engage in a semantic segmentation challenge for land cover description using multimodal remote sensing earth observation data, delving into real-world scenarios with a dataset comprising 70,000+ aerial imagery patches and 50,000 Sentinel-2 satellite acquisitions. Github : https://github.com/association-rosia/flair-2