#7683. Research on deep learning method for rail surface defect detection

October 2026publication date
Proposal available till 24-05-2025
4 total number of authors per manuscript0 $

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Journal’s subject area:
Electrical and Electronic Engineering;
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Abstract:
Rail surface defect detection plays a critical role in the maintenance of the rail transportation system. Video analysis technology is a promising method to detect defects due to its low cost and effectiveness. Recently, classification methods with complex deep convolutional networks have become popular. Despite their high accuracy, these methods cannot meet the requirements of defects localisation and real-time processing in practice. To solve these problems, this study proposes a novel object detection algorithm to detect rail defects.
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