Aircraft Type Identification Using Reinforcement Active Learning

As a subclass of Automatic Target Recognition problem, Automatic Aircraft Recognition plays an important role in air traffic management and modern battlefield for automatic monitoring and detection. The research on Automatic Aircraft Recognition is still in the exploratory stage. Since aircrafts move at high speeds in complex background, it is still a challenging task of fast data processing and accurate aircraft type recognition. Besides, active learning has recently attracted many researcher’s interesting. Based on this, we employ a learning-based approach which combines active learning with reinforcement learning to learn how and when to request labels for the aircraft type recognition problem. The experimental results show that the model can achieve a good prediction accuracy with few label requests.