Source Detection

Source detection encompasses the identification and localization of objects or events within various data types, ranging from astronomical images and audio signals to social network graphs and digital videos. Current research emphasizes the application of deep learning, employing architectures like 3D-Unet, YOLO, transformers, and recurrent neural networks, to improve accuracy and efficiency in diverse domains. These advancements are crucial for addressing challenges in fields like astronomy (e.g., identifying faint celestial objects), communication (e.g., pinpointing interference sources), and forensics (e.g., authenticating video sources), ultimately enhancing data analysis and interpretation across multiple scientific disciplines.