ALADDIN partner, CERTH is currently working on co-editing a Special Issue on UAV detection, classification and tracking using deep learning methods, with regards to the ALADDIN project. The “Deep Learning Based UAV Detection, Classification, and Tracking” Special Issue aims to highlight advances in the field of UAV detection, classification, and tracking using a variety of single and multi-sensor techniques based on deep learning. Artificial intelligence and deep learning techniques in conjunction with hardware innovations have significantly improved the capabilities to detect and classify drones, while counter-UAV systems are facing challenges to detect threats from diverse UAV types and makes, in diverse and ever-changing environments. Topics include, but are not limited to:
- Visual UAV detection and classification;
- IR UAV detection and classification;
- Radar UAV detection and classification;
- RF UAV detection and classification;
- Data fusion for UAV detection and classification;
- UAV tracking.
Additional information regarding the topic can be found here.