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The vehicle detection project competed in YOLO (You Only Look Once), a real-time object detection system. Using Python, the project aimed to accurately detect and classify vehicles in various scenarios. It involved collecting and annotating a dataset, implementing the YOLO architecture, and fine-tuning the model using transfer learning.

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amiruzzaman1/Vehicle-Detection-from-Traffic

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Vehicle-Detection-from-Traffic

The vehicle detection project competed in YOLO (You Only Look Once), a real-time object detection system. Using Python, the project aimed to accurately detect and classify vehicles in various scenarios. It involved collecting and annotating a dataset, implementing the YOLO architecture, and fine-tuning the model using transfer learning. The trained model was then evaluated for its ability to detect vehicles in real-time.

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The vehicle detection project competed in YOLO (You Only Look Once), a real-time object detection system. Using Python, the project aimed to accurately detect and classify vehicles in various scenarios. It involved collecting and annotating a dataset, implementing the YOLO architecture, and fine-tuning the model using transfer learning.

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