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Lightweight UAV Explosion Detection Dataset

AeroBlast-Vision: Lightweight UAV Explosion Detection Dataset Overview This dataset contains image frames and corresponding bounding box annotations for training lightweight deep learning object detection models . It was developed to provide early warning detection of localised anomalies, specifically focusing on combustion and explosions. The dataset is optimized for Unmanned Aerial Vehicles (UAVs) and real-time inference on edge computing devices. Dataset Details Image Count: 8179 Annotation Format: YOLO (.txt files) Classes: 0: Explosion Data Split : 70 % Train, 20% Valid, 10% Test Edge Deployment & Hardware This dataset is specifically st

Khan, Zaryab Ahmad, wazir, Irum Nigar
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