A Review of YOLO Algorithm Application in Object Detection in Complex Traffic Environments

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Detection accuracy has improved due to optimizations like attention mechanisms and feature fusion.
YOLO algorithm applications face challenges from occlusion, illumination, and weather conditions.
Recent methods have enhanced model robustness and real-time response in various traffic scenarios.
Future improvements in YOLO models may further support intelligent transportation system development.

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Literature review highlights improvements in detection accuracy and challenges in complex traffic environments.

Zebin Luo (2025) studied this question.

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