Deep-learning object detection for detecting humans and wildlife from aerial thermal imagery using YOLO models, deployed through a web interface.
Monitoring wildlife in large conservation areas is challenging due to limited visibility and wide geographic coverage. Manual observation often fails to detect animals or humans in nighttime conditions or dense environments.
Developed an AI-powered object-detection system using YOLO models trained on UAV thermal imagery. The system integrates a FastAPI backend and a web interface that lets users upload images and automatically detect objects with bounding-box visualization.
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