Fine-Tuning SAM for Land Cover Classification

Created using ChatSlide

This presentation explores the SAM model for effective land cover segmentation. It provides an introduction to the model and its objective, followed by the methodology, including fine-tuning steps and training phases with a classification head. Furthermore, it discusses the application of SAM for generating predictions, highlights the scalability benefits of Vision Transformers (ViT), and outlines future prospects and expansions for improving performance and adaptability.