Drone-type-Set: Drone Types Detection Benchmark for Drone Detection and Tracking

The Unmanned Aerial Vehicles (UAVs) market has been significantly growing andConsidering the availability of drones at low-cost prices the possibility ofmisusing them, for illegal purposes such as drug trafficking, spying, andterrorist attacks posing high risks to national security, is rising. Therefore,detecting and tracking unauthorized drones to prevent future attacks thatthreaten lives, facilities, and security, become a necessity. Drone detectioncan be performed using different sensors, while image-based detection is one ofthem due to the development of artificial intelligence techniques. However,knowing unauthorized drone types is one of the challenges due to the lack ofdrone types datasets. For that, in this paper, we provide a dataset of variousdrones as well as a comparison of recognized object detection models on theproposed dataset including YOLO algorithms with their different versions, like,v3, v4, and v5 along with the Detectronv2. The experimental results ofdifferent models are provided along with a description of each method. Thecollected dataset can be found inhttps://drive.google.com/drive/folders/1EPOpqlF4vG7hp4MYnfAecVOsdQ2JwBEd?usp=share_link