Deep Learning Models in Image-based Classification for Aquatic Biomonitoring

My doctoral research investigates the transferability assumptions in machine learning models, focusing on deep learning techniques. I aim to develop and enhance transfer learning and domain adaptation methodologies under complex assumptions. By conducting both theoretical and practical studies on aquatic images in computer vision, I seek to create more robust and generalizable models.