{"id":"https://openalex.org/W4412099966","doi":"https://doi.org/10.1145/3725949.3725951","title":"YOLOv9-GHP: Pothole Surface Defect Detection Algorithm Based on YOLOv9","display_name":"YOLOv9-GHP: Pothole Surface Defect Detection Algorithm Based on YOLOv9","publication_year":2024,"publication_date":"2024-11-22","ids":{"openalex":"https://openalex.org/W4412099966","doi":"https://doi.org/10.1145/3725949.3725951"},"language":"en","primary_location":{"id":"doi:10.1145/3725949.3725951","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3725949.3725951","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2024 7th International Conference on Sensors, Signal and Image Processing","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101412640","display_name":"Ming Chen","orcid":"https://orcid.org/0009-0001-1487-7634"},"institutions":[{"id":"https://openalex.org/I4210149102","display_name":"Sanya University","ror":"https://ror.org/04fa2qd52","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210149102"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Ming Chen","raw_affiliation_strings":["School of Information and Intelligent Engineering, University of Sanya, Sanya, Hainan, China"],"raw_orcid":"https://orcid.org/0009-0001-1487-7634","affiliations":[{"raw_affiliation_string":"School of Information and Intelligent Engineering, University of Sanya, Sanya, Hainan, China","institution_ids":["https://openalex.org/I4210149102"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Chunping Wang","orcid":"https://orcid.org/0009-0008-7857-3278"},"institutions":[{"id":"https://openalex.org/I4210149102","display_name":"Sanya University","ror":"https://ror.org/04fa2qd52","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210149102"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chunping Wang","raw_affiliation_strings":["School of Information and Intelligent Engineering, University of Sanya, Sanya, Hainan, China"],"raw_orcid":"https://orcid.org/0009-0008-7857-3278","affiliations":[{"raw_affiliation_string":"School of Information and Intelligent Engineering, University of Sanya, Sanya, Hainan, China","institution_ids":["https://openalex.org/I4210149102"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100451632","display_name":"Ying Yu","orcid":"https://orcid.org/0000-0001-7840-9891"},"institutions":[{"id":"https://openalex.org/I4210149102","display_name":"Sanya University","ror":"https://ror.org/04fa2qd52","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210149102"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ying Yu","raw_affiliation_strings":["School of Information and Intelligent Engineering, University of Sanya, Sanya, Hainan, China"],"raw_orcid":"https://orcid.org/0000-0001-7840-9891","affiliations":[{"raw_affiliation_string":"School of Information and Intelligent Engineering, University of Sanya, Sanya, Hainan, China","institution_ids":["https://openalex.org/I4210149102"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5101412640"],"corresponding_institution_ids":["https://openalex.org/I4210149102"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.43701129,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"7","last_page":"14"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9988999962806702,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing 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/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9988999962806702,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing 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/T11606","display_name":"Infrastructure Maintenance and Monitoring","score":0.9962999820709229,"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":0.9911999702453613,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/pothole","display_name":"Pothole (geology)","score":0.9692165851593018},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.559596061706543},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.455921471118927},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.14135485887527466}],"concepts":[{"id":"https://openalex.org/C2776023743","wikidata":"https://www.wikidata.org/wiki/Q7234907","display_name":"Pothole (geology)","level":2,"score":0.9692165851593018},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.559596061706543},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.455921471118927},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.14135485887527466},{"id":"https://openalex.org/C5900021","wikidata":"https://www.wikidata.org/wiki/Q163082","display_name":"Petrology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3725949.3725951","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3725949.3725951","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2024 7th International Conference on Sensors, Signal and Image Processing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W2099531274","https://openalex.org/W2592426749","https://openalex.org/W2748746495","https://openalex.org/W2969350702","https://openalex.org/W3020469381","https://openalex.org/W4280630824","https://openalex.org/W4293776518","https://openalex.org/W4382193354","https://openalex.org/W4382401167","https://openalex.org/W4384207671","https://openalex.org/W4390672982","https://openalex.org/W4399850700","https://openalex.org/W4399913728","https://openalex.org/W6600741150","https://openalex.org/W6607944259"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W4394960179","https://openalex.org/W2185993565","https://openalex.org/W4398789280","https://openalex.org/W1972815933","https://openalex.org/W2592426749","https://openalex.org/W2383269480","https://openalex.org/W3118927687"],"abstract_inverted_index":{"Road":[0],"potholes":[1,20],"represent":[2],"a":[3,55],"significant":[4],"hazard":[5],"in":[6,68,182],"the":[7,46,63,69,75,88,101,108,112,117,126,129,134,172,176],"field":[8],"of":[9,48,77,123,128,162],"traffic":[10],"safety,":[11],"and":[12,38,50,115,145,148,159,164,184],"their":[13],"potential":[14],"dangers":[15],"cannot":[16],"be":[17],"ignored.":[18],"These":[19],"not":[21,72],"only":[22,73],"pose":[23],"serious":[24],"threats":[25],"to":[26,30,90,119,136,178,192],"moving":[27],"vehicles,":[28],"leading":[29],"mechanical":[31],"failures":[32],"such":[33],"as":[34],"abnormal":[35],"tire":[36],"wear":[37],"suspension":[39],"system":[40,174],"damage,":[41],"but":[42,79],"they":[43],"also":[44,80],"undermine":[45],"safety":[47],"drivers":[49],"passengers.":[51],"This":[52,86],"paper":[53],"proposes":[54],"pothole":[56],"surface":[57],"defect":[58],"detection":[59,131],"algorithm,":[60],"YOLOv9-GHP.":[61],"Firstly,":[62],"C3Ghost":[64],"module":[65],"is":[66,104],"introduced":[67],"backbone,":[70],"which":[71,106],"reduces":[74],"number":[76],"parameters":[78],"enhances":[81,116],"multi-scale":[82],"feature":[83],"fusion":[84],"capabilities.":[85],"allows":[87],"model":[89,135,150,154],"capture":[91,137],"semantic":[92],"information":[93,191],"at":[94],"different":[95],"levels,":[96],"improving":[97,149],"its":[98],"performance.":[99],"Secondly,":[100],"HWD-ADown":[102],"downsampling":[103],"introduced,":[105],"increases":[107],"network":[109],"depth,":[110],"extends":[111],"receptive":[113],"field,":[114],"ability":[118],"extract":[120],"deep":[121],"features":[122],"defects.":[124],"Lastly,":[125],"addition":[127],"P2":[130],"layer":[132],"enables":[133],"small":[138],"defects":[139],"with":[140,175],"high":[141],"accuracy,":[142],"reducing":[143],"missed":[144],"false":[146],"detections":[147],"precision.":[151],"The":[152,167],"improved":[153],"achieves":[155],"an":[156],"average":[157],"precision":[158],"recall":[160],"rate":[161],"80.8%":[163],"71.6%,":[165],"respectively.":[166],"integrated":[168],"YOLOv9":[169],"algorithm":[170],"endows":[171],"monitoring":[173],"capability":[177],"process":[179],"image":[180],"data":[181],"real-time":[183],"identify":[185],"road":[186,193],"potholes,":[187],"providing":[188],"timely":[189],"warning":[190],"maintenance":[194],"teams.":[195]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
