RoMA: Scaling up Mamba-based Foundation Models for Remote Sensing
PositiveArtificial Intelligence
Recent advancements in self-supervised learning for Vision Transformers have led to significant breakthroughs in remote sensing foundation models. The Mamba architecture, with its linear complexity, presents a promising solution to the scalability issues posed by traditional self-attention methods, especially for large models and high-resolution images.
— Curated by the World Pulse Now AI Editorial System




