Meteor Detection

Meteor detection research focuses on automating the identification and tracking of meteors from video and other sensor data, primarily to improve the efficiency and accuracy of meteor studies. Current efforts leverage deep learning, particularly convolutional neural networks (CNNs), often incorporating techniques like transfer learning and Grad-CAM for precise meteor localization and classification within complex backgrounds. This automated analysis is crucial for accelerating scientific discovery, enabling large-scale meteor shower mapping, and facilitating the recovery of meteorites, ultimately enhancing our understanding of the solar system.