Crater Detection

Crater detection research focuses on automatically identifying and characterizing impact craters in planetary imagery, primarily to aid in spacecraft navigation, geological mapping, and understanding planetary evolution. Current efforts leverage deep learning architectures like YOLO and Mask R-CNN, often incorporating attention mechanisms for improved accuracy and explainability, and are exploring techniques for handling varying image resolutions, lighting conditions, and off-nadir viewing angles. These advancements are crucial for autonomous navigation in challenging extraterrestrial environments and for generating more efficient and accurate planetary datasets, improving the speed and reliability of scientific analysis.