{"id":"https://openalex.org/W2788468301","doi":"https://doi.org/10.1109/icip.2018.8451360","title":"Co-Occurrence Matrix Analysis-Based Semi-Supervised Training for Object Detection","display_name":"Co-Occurrence Matrix Analysis-Based Semi-Supervised Training for Object Detection","publication_year":2018,"publication_date":"2018-09-07","ids":{"openalex":"https://openalex.org/W2788468301","doi":"https://doi.org/10.1109/icip.2018.8451360","mag":"2788468301"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2018.8451360","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2018.8451360","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 25th IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1802.06964","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5000459808","display_name":"Min-Kook Choi","orcid":"https://orcid.org/0000-0001-7610-631X"},"institutions":[{"id":"https://openalex.org/I193352282","display_name":"Daegu Gyeongbuk Institute of Science and Technology","ror":"https://ror.org/03frjya69","country_code":"KR","type":"education","lineage":["https://openalex.org/I193352282"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Min-Kook Choi","raw_affiliation_strings":["DGIST, Daegu, Republic of Korea","DGIST, Daegu, Republic of Korea.#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"DGIST, Daegu, Republic of Korea","institution_ids":["https://openalex.org/I193352282"]},{"raw_affiliation_string":"DGIST, Daegu, Republic of Korea.#TAB#","institution_ids":["https://openalex.org/I193352282"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054297278","display_name":"Jaehyeong Park","orcid":"https://orcid.org/0000-0001-6622-3619"},"institutions":[{"id":"https://openalex.org/I193352282","display_name":"Daegu Gyeongbuk Institute of Science and Technology","ror":"https://ror.org/03frjya69","country_code":"KR","type":"education","lineage":["https://openalex.org/I193352282"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jaehyeong Park","raw_affiliation_strings":["DGIST, Daegu, Republic of Korea","DGIST, Daegu, Republic of Korea.#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"DGIST, Daegu, Republic of Korea","institution_ids":["https://openalex.org/I193352282"]},{"raw_affiliation_string":"DGIST, Daegu, Republic of Korea.#TAB#","institution_ids":["https://openalex.org/I193352282"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101816256","display_name":"Jihun Jung","orcid":"https://orcid.org/0000-0003-1667-9305"},"institutions":[{"id":"https://openalex.org/I193352282","display_name":"Daegu Gyeongbuk Institute of Science and Technology","ror":"https://ror.org/03frjya69","country_code":"KR","type":"education","lineage":["https://openalex.org/I193352282"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jihun Jung","raw_affiliation_strings":["DGIST, Daegu, Republic of Korea","DGIST, Daegu, Republic of Korea.#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"DGIST, Daegu, Republic of Korea","institution_ids":["https://openalex.org/I193352282"]},{"raw_affiliation_string":"DGIST, Daegu, Republic of Korea.#TAB#","institution_ids":["https://openalex.org/I193352282"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064276223","display_name":"Heechul Jung","orcid":"https://orcid.org/0000-0002-3005-2560"},"institutions":[{"id":"https://openalex.org/I157485424","display_name":"Korea Advanced Institute of Science and Technology","ror":"https://ror.org/05apxxy63","country_code":"KR","type":"education","lineage":["https://openalex.org/I157485424"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Heechul Jung","raw_affiliation_strings":["KAIST, Daejeon, Republic of Korea","KAIST,Daejeon,Republic of Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"KAIST, Daejeon, Republic of Korea","institution_ids":["https://openalex.org/I157485424"]},{"raw_affiliation_string":"KAIST,Daejeon,Republic of Korea","institution_ids":["https://openalex.org/I157485424"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100424012","display_name":"Jinhee Lee","orcid":"https://orcid.org/0000-0001-7542-8560"},"institutions":[{"id":"https://openalex.org/I193352282","display_name":"Daegu Gyeongbuk Institute of Science and Technology","ror":"https://ror.org/03frjya69","country_code":"KR","type":"education","lineage":["https://openalex.org/I193352282"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jin-Hee Lee","raw_affiliation_strings":["DGIST, Daegu, Republic of Korea","DGIST, Daegu, Republic of Korea.#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"DGIST, Daegu, Republic of Korea","institution_ids":["https://openalex.org/I193352282"]},{"raw_affiliation_string":"DGIST, Daegu, Republic of Korea.#TAB#","institution_ids":["https://openalex.org/I193352282"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110181565","display_name":"Woong Jae Won","orcid":null},"institutions":[{"id":"https://openalex.org/I193352282","display_name":"Daegu Gyeongbuk Institute of Science and Technology","ror":"https://ror.org/03frjya69","country_code":"KR","type":"education","lineage":["https://openalex.org/I193352282"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Woong-Jae Won","raw_affiliation_strings":["DGIST, Daegu, Republic of Korea","DGIST, Daegu, Republic of Korea.#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"DGIST, Daegu, Republic of Korea","institution_ids":["https://openalex.org/I193352282"]},{"raw_affiliation_string":"DGIST, Daegu, Republic of Korea.#TAB#","institution_ids":["https://openalex.org/I193352282"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102128481","display_name":"Woo Young Jung","orcid":null},"institutions":[{"id":"https://openalex.org/I193352282","display_name":"Daegu Gyeongbuk Institute of Science and Technology","ror":"https://ror.org/03frjya69","country_code":"KR","type":"education","lineage":["https://openalex.org/I193352282"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Woo Young Jung","raw_affiliation_strings":["DGIST, Daegu, Republic of Korea","DGIST, Daegu, Republic of Korea.#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"DGIST, Daegu, Republic of Korea","institution_ids":["https://openalex.org/I193352282"]},{"raw_affiliation_string":"DGIST, Daegu, Republic of Korea.#TAB#","institution_ids":["https://openalex.org/I193352282"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101714361","display_name":"Jin-Cheol Kim","orcid":"https://orcid.org/0000-0003-4375-9239"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jincheol Kim","raw_affiliation_strings":["SK Telecom, Seoul, Republic of Korea","[SK Telecom, Seoul, Republic of Korea]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"SK Telecom, Seoul, Republic of Korea","institution_ids":[]},{"raw_affiliation_string":"[SK Telecom, Seoul, Republic of Korea]","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5110077265","display_name":"Soon Kwon","orcid":null},"institutions":[{"id":"https://openalex.org/I193352282","display_name":"Daegu Gyeongbuk Institute of Science and Technology","ror":"https://ror.org/03frjya69","country_code":"KR","type":"education","lineage":["https://openalex.org/I193352282"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Soon Kwon","raw_affiliation_strings":["DGIST, Daegu, Republic of Korea","DGIST, Daegu, Republic of Korea.#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"DGIST, Daegu, Republic of Korea","institution_ids":["https://openalex.org/I193352282"]},{"raw_affiliation_string":"DGIST, Daegu, Republic of Korea.#TAB#","institution_ids":["https://openalex.org/I193352282"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":9,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0121936,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1333","last_page":"1337"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":1.0,"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":1.0,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9980999827384949,"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":0.9977999925613403,"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":0.8239556550979614},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7531832456588745},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7016953229904175},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.677824854850769},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6428334712982178},{"id":"https://openalex.org/keywords/annotation","display_name":"Annotation","score":0.599138617515564},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.5809871554374695},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.551903486251831},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.5363316535949707},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.45945268869400024},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.4348739981651306},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.43112897872924805},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.42596152424812317},{"id":"https://openalex.org/keywords/labeled-data","display_name":"Labeled data","score":0.4252161681652069},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.4181503653526306},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3426430821418762}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8239556550979614},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7531832456588745},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7016953229904175},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.677824854850769},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6428334712982178},{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.599138617515564},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5809871554374695},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.551903486251831},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.5363316535949707},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.45945268869400024},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.4348739981651306},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.43112897872924805},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.42596152424812317},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.4252161681652069},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.4181503653526306},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3426430821418762},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","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}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/icip.2018.8451360","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2018.8451360","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 25th IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1802.06964","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1802.06964","pdf_url":"https://arxiv.org/pdf/1802.06964","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"mag:2788468301","is_oa":true,"landing_page_url":"http://export.arxiv.org/pdf/1802.06964","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.1802.06964","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1802.06964","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":"pmh:oai:arXiv.org:1802.06964","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1802.06964","pdf_url":"https://arxiv.org/pdf/1802.06964","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[{"score":0.41999998688697815,"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2788468301.pdf","grobid_xml":"https://content.openalex.org/works/W2788468301.grobid-xml"},"referenced_works_count":24,"referenced_works":["https://openalex.org/W2117539524","https://openalex.org/W2168356304","https://openalex.org/W2194775991","https://openalex.org/W2340897893","https://openalex.org/W2407521645","https://openalex.org/W2570343428","https://openalex.org/W2601564443","https://openalex.org/W2743473392","https://openalex.org/W2950477723","https://openalex.org/W2952122856","https://openalex.org/W2952865063","https://openalex.org/W2953106684","https://openalex.org/W2953139137","https://openalex.org/W2963351448","https://openalex.org/W2963446712","https://openalex.org/W2963703618","https://openalex.org/W3106250896","https://openalex.org/W6620707391","https://openalex.org/W6639102338","https://openalex.org/W6714138976","https://openalex.org/W6715287400","https://openalex.org/W6733905022","https://openalex.org/W6743446608","https://openalex.org/W6785652829"],"related_works":["https://openalex.org/W2963280961","https://openalex.org/W2016016818","https://openalex.org/W2981118382","https://openalex.org/W3027136978","https://openalex.org/W3038090612","https://openalex.org/W2102605133","https://openalex.org/W2910827904","https://openalex.org/W2740667773","https://openalex.org/W2951267175","https://openalex.org/W2771673973","https://openalex.org/W3119344692","https://openalex.org/W586034241","https://openalex.org/W349740100","https://openalex.org/W2789575079","https://openalex.org/W3010618895","https://openalex.org/W2984303785","https://openalex.org/W2956946509","https://openalex.org/W2604333948","https://openalex.org/W2924319258","https://openalex.org/W3017812681"],"abstract_inverted_index":{"One":[0],"of":[1,19,56,59,120,143,163],"the":[2,17,32,77,83,92,101,121,125,128,131,141,144,164,183,189,195],"most":[3],"important":[4],"factors":[5],"in":[6,26,130],"training":[7,48],"object":[8,27,51,156],"recognition":[9],"networks":[10,14,151],"using":[11,188],"convolutional":[12],"neural":[13,150],"(CNN)":[15],"is":[16,80,87],"provision":[18],"annotated":[20,70],"data":[21,61],"accompanying":[22],"human":[23,37],"judgment.":[24],"Particularly,":[25],"detection":[28,137],"or":[29,193],"semantic":[30],"segmentation,":[31],"annotation":[33],"process":[34],"requires":[35],"considerable":[36],"effort.":[38],"In":[39],"this":[40],"paper,":[41],"we":[42,104],"propose":[43,105],"a":[44,64,96,106],"semi-supervised":[45],"learning":[46],"(SSL)-based":[47],"methodology":[49],"for":[50,90,158],"detection,":[52],"which":[53],"makes":[54],"use":[55],"automatic":[57],"labeling":[58],"un-annotated":[60],"by":[62,76,182],"applying":[63],"network":[65,79,196],"previously":[66],"trained":[67,78],"from":[68],"an":[69,73,135,155],"dataset.":[71],"Because":[72],"inferred":[74,98],"label":[75,99,123],"dependent":[81],"on":[82,110],"learned":[84],"parameters,":[85],"it":[86],"often":[88],"meaningless":[89],"re-training":[91],"network.":[93],"To":[94],"transfer":[95],"valuable":[97],"to":[100,139],"unlabeled":[102],"data,":[103],"re-alignment":[107],"method":[108,147,186],"based":[109],"co-occurrence":[111],"matrix":[112],"analysis":[113],"that":[114],"takes":[115],"into":[116],"account":[117],"one-hot-vector":[118],"encoding":[119],"estimated":[122],"and":[124,148,172],"correlation":[126],"between":[127],"objects":[129],"image.":[132],"We":[133],"used":[134],"MS-COCO":[136],"dataset":[138],"verify":[140],"performance":[142,162],"proposed":[145,184],"SSL":[146,185],"deformable":[149],"(D-ConvNets)":[152],"[1]":[153],"as":[154],"detector":[157,176],"basic":[159],"training.":[160],"The":[161],"existing":[165],"state-of-the-art":[166],"detectors":[167],"(D-ConvNets,":[168],"YOLO":[169],"v2":[170],"[2],":[171],"single":[173],"shot":[174],"multi-box":[175],"(SSD)":[177],"[3])":[178],"can":[179],"be":[180],"improved":[181],"without":[187],"additional":[190],"model":[191],"parameter":[192],"modifying":[194],"architecture.":[197]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
