New Large Scale 3D Asteroid

Recent research focuses on developing advanced methods for detecting, classifying, and characterizing large-scale 3D asteroid models, primarily leveraging machine learning and deep learning techniques such as convolutional neural networks (CNNs), recurrent neural networks (RNNs), and support vector machines (SVMs). These efforts aim to improve asteroid detection in various observational datasets (e.g., twilight surveys, microlensing data), enhance orbit classification accuracy, and enable more efficient autonomous navigation and resource utilization in future space missions. The development of large-scale 3D asteroid datasets and improved algorithms are crucial for advancing our understanding of asteroid composition, dynamics, and potential hazards.