Small Aerial Target Detection

Small aerial target detection focuses on reliably identifying small objects, such as drones or missiles, in airborne infrared imagery, a task complicated by rapid target movement and cluttered backgrounds. Recent research emphasizes the use of machine learning models, particularly boosted tree algorithms like LightGBM, often combined with trajectory analysis to filter false positives and improve detection accuracy. This field is crucial for enhancing national security and civilian applications by improving surveillance and threat assessment capabilities.