Analysis of vehicle and pedestrian recognition algorithm based on improved YOLO

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The improved YOLO algorithm significantly enhances detection performance by addressing shortcomings in feature recognition.
The approach involves implementing Feature Pyramid Network and replacing the original classification loss with Focal Loss.
Through multi-layer convolutional layers, the algorithm extracts features, enabling better small target recognition.
The enhancements aim to refine vehicle and pedestrian recognition accuracy, indicating advancements in computer vision technology.

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Algorithm improves detection performance in vehicle pedestrian recognition, suggesting new loss functions and FPN integration.

Liu et al. (2025) studied this question.

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