{"id":"https://openalex.org/W7156740308","doi":"https://doi.org/10.48550/arxiv.2604.24616","title":"Infrastructure-Guided Connectivity-Enhanced Road Crack Detection and Estimation","display_name":"Infrastructure-Guided Connectivity-Enhanced Road Crack Detection and Estimation","publication_year":2026,"publication_date":"2026-04-27","ids":{"openalex":"https://openalex.org/W7156740308","doi":"https://doi.org/10.48550/arxiv.2604.24616"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.24616","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.24616","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2604.24616","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5104347538","display_name":"Haosong Xiao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiao, Haosong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134804208","display_name":"Yamini Ramesh","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ramesh, Yamini","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101808751","display_name":"Rishabh Shukla","orcid":"https://orcid.org/0000-0002-2314-6948"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shukla, Rishabh","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134819131","display_name":"Swarat Sarkar","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sarkar, Swarat","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5064714785","display_name":"Chaozhe R. He","orcid":"https://orcid.org/0000-0002-0299-8412"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"He, Chaozhe R.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11606","display_name":"Infrastructure Maintenance and Monitoring","score":0.9721999764442444,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11606","display_name":"Infrastructure Maintenance and Monitoring","score":0.9721999764442444,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.017500000074505806,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10534","display_name":"Structural Health Monitoring Techniques","score":0.0010000000474974513,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.6531000137329102},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.6111999750137329},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.40369999408721924},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.36320000886917114},{"id":"https://openalex.org/keywords/pipeline-transport","display_name":"Pipeline transport","score":0.3361000120639801},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.3158000111579895}],"concepts":[{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.6531000137329102},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.6111999750137329},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5763999819755554},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.40369999408721924},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3935000002384186},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3801000118255615},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.36320000886917114},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.34850001335144043},{"id":"https://openalex.org/C175309249","wikidata":"https://www.wikidata.org/wiki/Q725864","display_name":"Pipeline transport","level":2,"score":0.3361000120639801},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.31850001215934753},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.3158000111579895},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.3000999987125397},{"id":"https://openalex.org/C2780385302","wikidata":"https://www.wikidata.org/wiki/Q367158","display_name":"Protocol (science)","level":3,"score":0.2962999939918518},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.2831999957561493},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2777000069618225}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.24616","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.24616","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2604.24616","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.24616","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.6544471383094788}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3,80],"report":[4],"the":[5,31,36,39,52,58,82,90,100],"world's":[6],"first":[7,23],"infrastructure-guided":[8],"communication-enhanced":[9],"road":[10],"crack":[11,59,64],"detection":[12,60,65,92,101],"pipeline":[13,93],"that":[14],"is":[15],"effective":[16],"and":[17,49,68,103],"implementable":[18],"on":[19,94],"passenger":[20],"vehicles.":[21],"We":[22,88],"design":[24],"a":[25,69,74,78],"customized":[26],"communication":[27],"protocol":[28],"to":[29,38,57,84],"transmit":[30],"region":[32],"of":[33],"interest":[34],"from":[35],"infrastructure":[37],"vehicle.":[40],"With":[41],"proper":[42],"camera":[43],"image":[44],"processing":[45],"(e.g.,":[46],"dynamic":[47],"cropping":[48],"frame":[50],"selection),":[51],"focused":[53],"images":[54],"are":[55],"provided":[56],"model.":[61],"Leveraging":[62],"state-of-the-art":[63],"model":[66,83],"backbones":[67],"carefully":[70],"prepared":[71],"dataset":[72],"comprising":[73],"forward-facing":[75],"view":[76],"with":[77],"crack,":[79],"train":[81],"improve":[85],"crack-detection":[86],"performance.":[87],"demonstrate":[89],"full":[91],"an":[95],"experimental":[96],"vehicle":[97],"platform,":[98],"showcase":[99],"effectiveness,":[102],"project":[104],"future":[105],"research":[106],"directions.":[107]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-04-29T00:00:00"}