{"id":"https://openalex.org/W2887902357","doi":"https://doi.org/10.1109/tip.2018.2857407","title":"Vision-Based Parking-Slot Detection: A DCNN-Based Approach and a Large-Scale Benchmark Dataset","display_name":"Vision-Based Parking-Slot Detection: A DCNN-Based Approach and a Large-Scale Benchmark Dataset","publication_year":2018,"publication_date":"2018-07-18","ids":{"openalex":"https://openalex.org/W2887902357","doi":"https://doi.org/10.1109/tip.2018.2857407","mag":"2887902357","pmid":"https://pubmed.ncbi.nlm.nih.gov/30028704"},"language":"en","primary_location":{"id":"doi:10.1109/tip.2018.2857407","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2018.2857407","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Image Processing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5100351849","display_name":"Lin Zhang","orcid":"https://orcid.org/0000-0002-4360-5523"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Lin Zhang","raw_affiliation_strings":["Institute of Intelligent Vehicle, Tongji University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Institute of Intelligent Vehicle, Tongji University, Shanghai, China","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025522422","display_name":"Junhao Huang","orcid":null},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junhao Huang","raw_affiliation_strings":["School of Software Engineering, Tongji University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"School of Software Engineering, Tongji University, Shanghai, China","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101646969","display_name":"Xiyuan Li","orcid":"https://orcid.org/0000-0001-7135-9836"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiyuan Li","raw_affiliation_strings":["School of Software Engineering, Tongji University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"School of Software Engineering, Tongji University, Shanghai, China","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100379486","display_name":"Lu Xiong","orcid":"https://orcid.org/0000-0002-1673-2658"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lu Xiong","raw_affiliation_strings":["Institute of Intelligent Vehicle, Tongji University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Institute of Intelligent Vehicle, Tongji University, Shanghai, China","institution_ids":["https://openalex.org/I116953780"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100351849"],"corresponding_institution_ids":["https://openalex.org/I116953780"],"apc_list":null,"apc_paid":null,"fwci":8.937,"has_fulltext":false,"cited_by_count":128,"citation_normalized_percentile":{"value":0.98255799,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"27","issue":"11","first_page":"5350","last_page":"5364"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12546","display_name":"Smart Parking Systems Research","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"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/T12546","display_name":"Smart Parking Systems Research","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"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/T12707","display_name":"Vehicle License Plate Recognition","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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":0.996399998664856,"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/computer-science","display_name":"Computer science","score":0.7874571084976196},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7519686222076416},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.7040101289749146},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.6102470755577087},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6031183004379272},{"id":"https://openalex.org/keywords/parking-lot","display_name":"Parking lot","score":0.5405252575874329},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.49108195304870605},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.46564945578575134},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.45496541261672974},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.44523388147354126},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3839498460292816},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.0888819694519043},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.08201542496681213}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7874571084976196},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7519686222076416},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.7040101289749146},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.6102470755577087},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6031183004379272},{"id":"https://openalex.org/C2777427512","wikidata":"https://www.wikidata.org/wiki/Q6501349","display_name":"Parking lot","level":2,"score":0.5405252575874329},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.49108195304870605},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.46564945578575134},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.45496541261672974},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.44523388147354126},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3839498460292816},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0888819694519043},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.08201542496681213},{"id":"https://openalex.org/C147176958","wikidata":"https://www.wikidata.org/wiki/Q77590","display_name":"Civil engineering","level":1,"score":0.0},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tip.2018.2857407","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2018.2857407","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Image Processing","raw_type":"journal-article"},{"id":"pmid:30028704","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/30028704","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on image processing : a publication of the IEEE Signal Processing Society","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","score":0.6200000047683716,"display_name":"Industry, innovation and infrastructure"}],"awards":[{"id":"https://openalex.org/G1109949084","display_name":null,"funder_award_id":"2100219068","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G7735728778","display_name":null,"funder_award_id":"61672380","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":76,"referenced_works":["https://openalex.org/W247104752","https://openalex.org/W591992626","https://openalex.org/W593538679","https://openalex.org/W639708223","https://openalex.org/W1536680647","https://openalex.org/W1577784296","https://openalex.org/W1590183771","https://openalex.org/W1596591750","https://openalex.org/W1665214252","https://openalex.org/W1686810756","https://openalex.org/W1906375339","https://openalex.org/W1932198206","https://openalex.org/W1983047562","https://openalex.org/W2000431576","https://openalex.org/W2008549258","https://openalex.org/W2031454541","https://openalex.org/W2032322171","https://openalex.org/W2034779469","https://openalex.org/W2050254124","https://openalex.org/W2078798748","https://openalex.org/W2097117768","https://openalex.org/W2097543505","https://openalex.org/W2098517398","https://openalex.org/W2101117085","https://openalex.org/W2102605133","https://openalex.org/W2108598243","https://openalex.org/W2111308925","https://openalex.org/W2112365909","https://openalex.org/W2121553527","https://openalex.org/W2121796793","https://openalex.org/W2121929431","https://openalex.org/W2124324640","https://openalex.org/W2126653369","https://openalex.org/W2127391626","https://openalex.org/W2133026742","https://openalex.org/W2133648827","https://openalex.org/W2136591213","https://openalex.org/W2141464147","https://openalex.org/W2147800946","https://openalex.org/W2148143831","https://openalex.org/W2148412784","https://openalex.org/W2148690598","https://openalex.org/W2155912251","https://openalex.org/W2158525823","https://openalex.org/W2158579290","https://openalex.org/W2160115232","https://openalex.org/W2161969291","https://openalex.org/W2163605009","https://openalex.org/W2167667767","https://openalex.org/W2169325918","https://openalex.org/W2194775991","https://openalex.org/W2237407343","https://openalex.org/W2243397390","https://openalex.org/W2265516011","https://openalex.org/W2279098554","https://openalex.org/W2343144455","https://openalex.org/W2515679514","https://openalex.org/W2534262995","https://openalex.org/W2548197316","https://openalex.org/W2570343428","https://openalex.org/W2751406942","https://openalex.org/W2919115771","https://openalex.org/W2962835968","https://openalex.org/W2962992847","https://openalex.org/W2963037989","https://openalex.org/W3097096317","https://openalex.org/W3106250896","https://openalex.org/W6617818097","https://openalex.org/W6637242042","https://openalex.org/W6637373629","https://openalex.org/W6674676010","https://openalex.org/W6679089111","https://openalex.org/W6683537716","https://openalex.org/W6684191040","https://openalex.org/W6693508404","https://openalex.org/W6785652829"],"related_works":["https://openalex.org/W2378211422","https://openalex.org/W4321353415","https://openalex.org/W2745001401","https://openalex.org/W2130974462","https://openalex.org/W2028665553","https://openalex.org/W2086519370","https://openalex.org/W4246352526","https://openalex.org/W3126772657","https://openalex.org/W2909750883","https://openalex.org/W3025757700"],"abstract_inverted_index":{"In":[0,43,77],"the":[1,26,34,51,68,112,116,127,130,163,178,198,225,230],"automobile":[2],"industry,":[3],"recent":[4],"years":[5],"have":[6,211,232],"witnessed":[7],"a":[8,37,97,169],"growing":[9],"interest":[10],"in":[11,57,123,180],"developing":[12],"self-parking":[13],"systems.":[14],"For":[15,195],"such":[16,49],"systems,":[17],"how":[18],"to":[19,82,86,161],"accurately":[20],"and":[21,24,39,60,89,133,191,200,207,229],"efficiently":[22],"detect":[23],"localize":[25],"parking-slots":[27,201],"defined":[28],"by":[29,64,139,156],"regular":[30],"line":[31],"segments":[32],"near":[33],"vehicle":[35],"is":[36,173,177],"key":[38,121],"still":[40],"unresolved":[41],"issue.":[42],"fact,":[44],"kinds":[45],"of":[46,53,141,146,165,209],"unfavorable":[47],"factors,":[48],"as":[50,115,148],"diversity":[52],"ground":[54],"materials,":[55],"changes":[56],"illumination":[58],"conditions,":[59],"unpredictable":[61],"shadows":[62],"caused":[63],"nearby":[65],"trees,":[66],"make":[67,219],"vision-based":[69,166],"parking-slot":[70,105,167],"detection":[71,106],"much":[72],"harder":[73],"than":[74],"it":[75],"looks.":[76],"this":[78,84,181],"paper,":[79],"we":[80,95],"attempt":[81],"solve":[83],"issue":[85],"some":[87],"extent":[88],"our":[90,215,220],"contributions":[91],"are":[92,119,202],"twofold.":[93],"First,":[94],"propose":[96],"novel":[98],"DCNN":[99,158],"(Deep":[100],"Convolutional":[101],"Neural":[102],"Networks)":[103],"based":[104],"approach,":[107],"namely":[108],"DeepPS,":[109,124],"which":[110,151],"takes":[111],"surround-view":[113,185],"image":[114,132,136],"input.":[117],"There":[118],"two":[120],"steps":[122],"identifying":[125],"all":[126,224],"marking-points":[128,199],"on":[129,214],"input":[131],"classifying":[134],"local":[135],"patterns":[137],"formed":[138],"pairs":[140],"markingpoints.":[142],"We":[143],"formulate":[144],"both":[145],"them":[147],"learning":[149],"problems,":[150],"can":[152],"be":[153],"solved":[154],"naturally":[155],"modern":[157],"models.":[159],"Second,":[160],"facilitate":[162],"study":[164],"detection,":[168],"largescale":[170],"labeled":[171],"dataset":[172,176,231],"established.":[174],"This":[175],"largest":[179],"field,":[182],"comprising":[183],"12,165":[184],"images":[186],"collected":[187,216],"from":[188],"typical":[189],"indoor":[190],"outdoor":[192],"parking":[193],"sites.":[194],"each":[196],"image,":[197],"carefully":[203],"labeled.":[204],"The":[205],"efficacy":[206],"efficiency":[208],"DeepPS":[210],"been":[212,233],"corroborated":[213],"dataset.":[217],"To":[218],"results":[221],"fully":[222],"reproducible,":[223],"relevant":[226],"source":[227],"codes":[228],"made":[234],"publicly":[235],"available":[236],"at":[237],"https://cslinzhang.github.io/deepps/.":[238]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":20},{"year":2024,"cited_by_count":14},{"year":2023,"cited_by_count":27},{"year":2022,"cited_by_count":20},{"year":2021,"cited_by_count":13},{"year":2020,"cited_by_count":19},{"year":2019,"cited_by_count":12},{"year":2018,"cited_by_count":2}],"updated_date":"2026-04-07T14:57:38.498316","created_date":"2025-10-10T00:00:00"}