RoadNet: Efficient Model to Detect and Classify Road Damages

نویسندگان

چکیده

Poorly maintained roads can cause lethal automobile accidents in various ways. Thus, detecting and reporting damaged parts of is one the most crucial road maintenance tasks, it vital to identify type severity damage help fix as soon possible. Several researchers have used computer vision detection algorithms detect classify damages, including cracking, distortion, disintegration. Providing automatic methods municipalities save time effort speed up operations. This study proposes a method its based on CNN trained newly curated dataset collected from Saudi roads. Hence, this also presents with labeled classes, which are cracks, potholes, depressions, shoving. The was collaboration employees municipality Rabigh Governorate using smartphone device reviewed by experts. In addition, several deep learning were implemented evaluated proposed dataset. found that custom (RoadNet) has higher accuracy than pre-trained models.

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ژورنال

عنوان ژورنال: Applied sciences

سال: 2022

ISSN: ['2076-3417']

DOI: https://doi.org/10.3390/app122211529