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This is a Quantitative Study study.

Detecting Road Depressions Based on Deep Learning Techniques

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This analysis demonstrates YOLOv12 enhances pothole detection accuracy in road infrastructure, suggesting efficiencies for public safety.

YOLOv12 achieved high detection rates for potholes, illustrating its potential for efficient road maintenance.
The model demonstrated superior performance metrics, with minimal false positives and high precision-recall scores.
Utilizing a custom dataset of 65 annotated video frames, YOLOv12 underwent effective training to boost detection capabilities.
Future applications may include real-time deployments on edge devices, indicating a leap towards smart infrastructure management.

Mohammed Basim Omar (2025) studied this question.

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