Automatic Defect Detection in Sewer Network Using Deep Learning Based Object Detector

arXiv:2404.06219v1 Announce Type: new
Abstract: Maintaining sewer systems in large cities is important, but also time and effort consuming, because visual inspections are currently done manually. To reduce the amount of aforementioned manual work, defects within sewer pipes should be located and classified automatically. In the past, multiple works have attempted solving this problem using classical image processing, machine learning, or a combination of those. However, each provided solution only focus on detecting a limited set of defect/structure types, such …

abstract arxiv cities cs.cv deep learning defect detection defects detection multiple network object reduce systems type visual work