{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/city-scale-road-audit-system-using-deep","title":"City-Scale Road Audit System using Deep Learning","arxiv_id":"1811.10210","date":"2018-11-26","proceeding":null,"authors":["Sudhir Yarram","Girish Varma","C. V. Jawahar"],"abstract":"Road networks in cities are massive and is a critical component of mobility.\nFast response to defects, that can occur not only due to regular wear and tear\nbut also because of extreme events like storms, is essential. Hence there is a\nneed for an automated system that is quick, scalable and cost-effective for\ngathering information about defects. We propose a system for city-scale road\naudit, using some of the most recent developments in deep learning and semantic\nsegmentation. For building and benchmarking the system, we curated a dataset\nwhich has annotations required for road defects. However, many of the labels\nrequired for road audit have high ambiguity which we overcome by proposing a\nlabel hierarchy. We also propose a multi-step deep learning model that segments\nthe road, subdivide the road further into defects, tags the frame for each\ndefect and finally localizes the defects on a map gathered using GPS. We\nanalyze and evaluate the models on image tagging as well as segmentation at\ndifferent levels of the label hierarchy.","url_abs":"http://arxiv.org/abs/1811.10210v1","url_pdf":"http://arxiv.org/pdf/1811.10210v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"city-scale-road-audit-system-using-deep","repo_url":"https://github.com/Sudhir11292rt/City-scale-Road-Audit","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"benchmarking","task_name":"Benchmarking"},{"task_slug":"deep-learning","task_name":"Deep Learning"},{"task_slug":"semantic-segmentation","task_name":"Semantic Segmentation"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}