This study explores the application of YOLOv8, a state-of-the-art object detection algorithm, for human detection in open water using drones in Search and Rescue (SAR) operations. Open water environments present unique challenges for human detection due to dynamic conditions, limited visibility, and the vastness of the area. Drones equipped with SAR sensors and YOLOv8 offer a promising solution to enhance the efficiency and effectiveness of search and rescue missions. The research involves the development of a specialized model based on YOLOv8 architecture, fine-tuned for human detection in open water scenarios. A dataset comprising diverse open water images is used for training and validation, ensuring the robustness of the model across various conditions. The drone's capabilities, including real-time data transmission and high maneuverability, are leveraged to conduct simulated SAR missions in open water environments.
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G et al. (2024) studied this question.
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