Introducing AOD 4: A dataset for air borne object detection
Vama Soni,
Dhruval Shah,
Jeel Joshi,
Shilpa Gite,
Biswajeet Pradhan,
Abdullah Alamri
Affiliations
Vama Soni
Department of Computer Science and Engineering, Devang Patel Institute of Advance of Technology and Research (DEPSTAR), Charotar University of Science and Technology (CHARUSAT), Changa, Gujarat, 388421, India
Dhruval Shah
Department of Information Technology, Devang Patel Institute of Advance of Technology and Research (DEPSTAR), Charotar University of Science and Technology (CHARUSAT), Changa, Gujarat, 388421, India
Jeel Joshi
Department of Information Technology, Devang Patel Institute of Advance of Technology and Research (DEPSTAR), Charotar University of Science and Technology (CHARUSAT), Changa, Gujarat, 388421, India
Shilpa Gite
Department of Artificial Intelligence and Machine Learning, Symbiosis Institute of Technology, Symbiosis Centre of Applied Artificial Intelligence (SCAAI), Symbiosis International (Deemed) University, Pune, 412115, India
Biswajeet Pradhan
Centre for Advanced Modelling and Geospatial Information Systems (CAMGIS), School of Civil and Environmental Engineering, University of Technology Sydney, NSW 2007, Australia; Corresponding author.
Abdullah Alamri
Department of Geology and Geophysics, College of Science, King Saud University, Riyadh, Saudi Arabia
This paper introduces an airborne object dataset comprising 22,516 images categorizing four classes of airborne objects: airplanes, helicopters, drones, and birds. The dataset was compiled from YouTube-8 M, Anti-UAV, and Ahmed Mohsen's dataset hosted on Roboflow. Videos were sourced from the first two platforms and converted into individual frames, whereas the latter dataset already consisted of images. Following collection, the dataset underwent labelling and annotation processes utilizing Roboflow's annotation tool, resulting in 7,900 annotations per class. Researchers can leverage this dataset to develop and refine algorithms for airborne object detection and tracking, with potential applications spanning military surveillance, border security, and public safety.
