{"id":"https://openalex.org/W2958609736","doi":"https://doi.org/10.1109/itsc.2019.8916901","title":"Semi-supervised Detector Training with Prototypes for Vehicle Detection","display_name":"Semi-supervised Detector Training with Prototypes for Vehicle Detection","publication_year":2019,"publication_date":"2019-10-01","ids":{"openalex":"https://openalex.org/W2958609736","doi":"https://doi.org/10.1109/itsc.2019.8916901","mag":"2958609736"},"language":"en","primary_location":{"id":"doi:10.1109/itsc.2019.8916901","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc.2019.8916901","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE Intelligent Transportation Systems Conference (ITSC)","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/A5078850158","display_name":"Georg Waltner","orcid":null},"institutions":[{"id":"https://openalex.org/I4092182","display_name":"Graz University of Technology","ror":"https://ror.org/00d7xrm67","country_code":"AT","type":"education","lineage":["https://openalex.org/I4092182"]}],"countries":["AT"],"is_corresponding":false,"raw_author_name":"Georg Waltner","raw_affiliation_strings":["Institute of Computer Graphics and Vision (ICG), Faculty of Computer Science, Graz University of Technology, Graz, Austria"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Computer Graphics and Vision (ICG), Faculty of Computer Science, Graz University of Technology, Graz, Austria","institution_ids":["https://openalex.org/I4092182"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071495978","display_name":"Michael Opitz","orcid":"https://orcid.org/0000-0002-6218-6723"},"institutions":[{"id":"https://openalex.org/I4092182","display_name":"Graz University of Technology","ror":"https://ror.org/00d7xrm67","country_code":"AT","type":"education","lineage":["https://openalex.org/I4092182"]}],"countries":["AT"],"is_corresponding":false,"raw_author_name":"Michael Opitz","raw_affiliation_strings":["Institute of Computer Graphics and Vision (ICG), Faculty of Computer Science, Graz University of Technology, Graz, Austria"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Computer Graphics and Vision (ICG), Faculty of Computer Science, Graz University of Technology, Graz, Austria","institution_ids":["https://openalex.org/I4092182"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090450230","display_name":"Georg Krispel","orcid":null},"institutions":[{"id":"https://openalex.org/I4092182","display_name":"Graz University of Technology","ror":"https://ror.org/00d7xrm67","country_code":"AT","type":"education","lineage":["https://openalex.org/I4092182"]}],"countries":["AT"],"is_corresponding":false,"raw_author_name":"Georg Krispel","raw_affiliation_strings":["Institute of Computer Graphics and Vision (ICG), Faculty of Computer Science, Graz University of Technology, Graz, Austria"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Computer Graphics and Vision (ICG), Faculty of Computer Science, Graz University of Technology, Graz, Austria","institution_ids":["https://openalex.org/I4092182"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039382695","display_name":"Horst Possegger","orcid":"https://orcid.org/0000-0002-5427-9938"},"institutions":[{"id":"https://openalex.org/I4092182","display_name":"Graz University of Technology","ror":"https://ror.org/00d7xrm67","country_code":"AT","type":"education","lineage":["https://openalex.org/I4092182"]}],"countries":["AT"],"is_corresponding":false,"raw_author_name":"Horst Possegger","raw_affiliation_strings":["Institute of Computer Graphics and Vision (ICG), Faculty of Computer Science, Graz University of Technology, Graz, Austria"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Computer Graphics and Vision (ICG), Faculty of Computer Science, Graz University of Technology, Graz, Austria","institution_ids":["https://openalex.org/I4092182"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5011359067","display_name":"Horst Bischof","orcid":"https://orcid.org/0000-0002-9096-6671"},"institutions":[{"id":"https://openalex.org/I4092182","display_name":"Graz University of Technology","ror":"https://ror.org/00d7xrm67","country_code":"AT","type":"education","lineage":["https://openalex.org/I4092182"]}],"countries":["AT"],"is_corresponding":false,"raw_author_name":"Horst Bischof","raw_affiliation_strings":["Institute of Computer Graphics and Vision (ICG), Faculty of Computer Science, Graz University of Technology, Graz, Austria"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Computer Graphics and Vision (ICG), Faculty of Computer Science, Graz University of Technology, Graz, Austria","institution_ids":["https://openalex.org/I4092182"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.06084369,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"4261","last_page":"4266"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9998999834060669,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9975000023841858,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9965000152587891,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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":0.8314236402511597},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7264522910118103},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.6576927900314331},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6418096423149109},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.639853835105896},{"id":"https://openalex.org/keywords/bounding-overwatch","display_name":"Bounding overwatch","score":0.5993797779083252},{"id":"https://openalex.org/keywords/minimum-bounding-box","display_name":"Minimum bounding box","score":0.5329027771949768},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5270008444786072},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5161939263343811},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5150008201599121},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5019237995147705},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.4980125427246094},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.49328964948654175},{"id":"https://openalex.org/keywords/precision-and-recall","display_name":"Precision and recall","score":0.4620925784111023},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.05702897906303406}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8314236402511597},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7264522910118103},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.6576927900314331},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6418096423149109},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.639853835105896},{"id":"https://openalex.org/C63584917","wikidata":"https://www.wikidata.org/wiki/Q333286","display_name":"Bounding overwatch","level":2,"score":0.5993797779083252},{"id":"https://openalex.org/C147037132","wikidata":"https://www.wikidata.org/wiki/Q6865426","display_name":"Minimum bounding box","level":3,"score":0.5329027771949768},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5270008444786072},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5161939263343811},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5150008201599121},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5019237995147705},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.4980125427246094},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.49328964948654175},{"id":"https://openalex.org/C81669768","wikidata":"https://www.wikidata.org/wiki/Q2359161","display_name":"Precision and recall","level":2,"score":0.4620925784111023},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.05702897906303406},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/itsc.2019.8916901","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc.2019.8916901","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE Intelligent Transportation Systems Conference (ITSC)","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":55,"referenced_works":["https://openalex.org/W318792885","https://openalex.org/W639708223","https://openalex.org/W1536680647","https://openalex.org/W1594098193","https://openalex.org/W1686810756","https://openalex.org/W1722318740","https://openalex.org/W1861492603","https://openalex.org/W1899185266","https://openalex.org/W2031489346","https://openalex.org/W2088049833","https://openalex.org/W2097117768","https://openalex.org/W2102605133","https://openalex.org/W2108598243","https://openalex.org/W2115699968","https://openalex.org/W2159291411","https://openalex.org/W2163605009","https://openalex.org/W2194775991","https://openalex.org/W2212123867","https://openalex.org/W2214409633","https://openalex.org/W2302255633","https://openalex.org/W2418676188","https://openalex.org/W2549139847","https://openalex.org/W2557728737","https://openalex.org/W2565639579","https://openalex.org/W2570343428","https://openalex.org/W2612445135","https://openalex.org/W2613718673","https://openalex.org/W2618530766","https://openalex.org/W2788159735","https://openalex.org/W2796438033","https://openalex.org/W2950800384","https://openalex.org/W2962835968","https://openalex.org/W2962997028","https://openalex.org/W2963163009","https://openalex.org/W2963351448","https://openalex.org/W2963490895","https://openalex.org/W2963603913","https://openalex.org/W2963996492","https://openalex.org/W3106250896","https://openalex.org/W4297775537","https://openalex.org/W6620707391","https://openalex.org/W6635419406","https://openalex.org/W6637373629","https://openalex.org/W6639102338","https://openalex.org/W6639927594","https://openalex.org/W6677245018","https://openalex.org/W6683633756","https://openalex.org/W6684191040","https://openalex.org/W6688353369","https://openalex.org/W6698183232","https://openalex.org/W6714138976","https://openalex.org/W6737664043","https://openalex.org/W6737976933","https://openalex.org/W6748931594","https://openalex.org/W6785652829"],"related_works":["https://openalex.org/W4237171675","https://openalex.org/W3036286480","https://openalex.org/W4287027631","https://openalex.org/W3192357901","https://openalex.org/W2387360586","https://openalex.org/W2952736415","https://openalex.org/W3209723314","https://openalex.org/W3205398323","https://openalex.org/W2883297582","https://openalex.org/W4390524233"],"abstract_inverted_index":{"Adapting":[0],"detectors":[1,32],"to":[2,77,111,126,134,146,205],"new":[3],"datasets":[4,54],"is":[5,21,68,74],"needed":[6],"in":[7,23,97],"scenarios":[8],"where":[9,26,88],"a":[10,13,24,27,86,90,98,129,148,157,169],"user":[11],"has":[12],"specific":[14],"dataset":[15,73,131,160],"that":[16,55,166,191],"contains":[17],"novel":[18],"classes":[19,163],"or":[20],"recorded":[22],"setting":[25],"pretrained":[28,208],"detector":[29,67],"fails.":[30],"While":[31],"based":[33],"on":[34,53,156,168],"Convolutional":[35],"Neural":[36],"Networks":[37],"(CNNs)":[38],"are":[39,93],"state-of-the-art":[40],"and":[41,164,185],"nowadays":[42],"publicly":[43],"available,":[44],"they":[45,61],"suffer":[46],"from":[47,58,107],"bad":[48],"generalization":[49],"capabilities":[50],"when":[51],"applied":[52],"notably":[56],"differ":[57],"the":[59,66,72,80,105,108,114],"one":[60],"were":[62],"trained":[63,120],"on.":[64],"Finetuning":[65],"only":[69,89],"possible":[70],"if":[71],"large":[75,130],"enough":[76],"not":[78],"destroy":[79],"underlying":[81],"feature":[82],"representation.":[83],"We":[84,152,188],"propose":[85],"method":[87,155],"few":[91,195],"prototypes":[92],"labeled":[94,198],"for":[95,210],"training":[96],"semi-supervised":[99],"manner.":[100],"In":[101],"particular,":[102],"we":[103,143,174],"separate":[104],"detection":[106],"classification":[109,122],"step":[110],"avoid":[112],"impairing":[113],"bounding":[115],"box":[116],"proposal":[117],"generation.":[118],"Our":[119],"prototype":[121],"network":[123],"provides":[124],"labels":[125],"automatically":[127],"source":[128],"containing":[132],"20":[133],"30":[135],"times":[136],"more":[137,149],"samples":[138,199],"without":[139],"further":[140,189],"supervision,":[141],"which":[142],"then":[144],"use":[145],"train":[147],"powerful":[150],"network.":[151],"evaluate":[153],"our":[154],"private":[158],"vehicle":[159],"with":[161,193],"six":[162],"show":[165,190],"evaluating":[167],"previously":[170],"unseen":[171],"recording":[172],"site":[173],"can":[175],"gain":[176],"an":[177],"accuracy":[178,203],"increase":[179],"of":[180],"9%":[181],"at":[182],"same":[183],"precision":[184],"recall":[186],"levels.":[187],"finetuning":[192],"as":[194,196],"25":[197],"per":[200],"class":[201],"doubles":[202],"compared":[204],"directly":[206],"using":[207],"features":[209],"nearest":[211],"neighbor":[212],"classification.":[213]},"counts_by_year":[{"year":2023,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
