The project "Enhancing Pollinator Conservation towards Agriculture 4.0: Monitoring of Bees through Object Recognition" seeks to create advanced object recognition algorithms capable of identifying individual bees and tracking their movements over time. This project uses state-of-the-art pretrained networks, such as YOLO, and unique data augmentation strategies to improve model performance with a comprehensive dataset of approximately 9664 annotated bee pictures. Furthermore, the study will investigate optimisation ways to cut classification time, allowing for analysis of video feeds.
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The project "Enhancing Pollinator Conservation towards Agriculture 4.0: Monitoring of Bees through Object Recognition" seeks to create advanced object recognition algorithms capable of identifying individual bees and tracking their movements over time.
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AjayJohnAlex/Bee_Detection
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The project "Enhancing Pollinator Conservation towards Agriculture 4.0: Monitoring of Bees through Object Recognition" seeks to create advanced object recognition algorithms capable of identifying individual bees and tracking their movements over time.
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