{"id":"https://openalex.org/W4392248441","doi":"https://doi.org/10.1109/icce59016.2024.10444242","title":"Improve Fine-grained Visual Classification Accuracy by Controllable Location Knowledge Distillation","display_name":"Improve Fine-grained Visual Classification Accuracy by Controllable Location Knowledge Distillation","publication_year":2024,"publication_date":"2024-01-06","ids":{"openalex":"https://openalex.org/W4392248441","doi":"https://doi.org/10.1109/icce59016.2024.10444242"},"language":"en","primary_location":{"id":"doi:10.1109/icce59016.2024.10444242","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icce59016.2024.10444242","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Consumer Electronics (ICCE)","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/A5101310720","display_name":"You-Lin Tsai","orcid":null},"institutions":[{"id":"https://openalex.org/I134161618","display_name":"National Taiwan Normal University","ror":"https://ror.org/059dkdx38","country_code":"TW","type":"education","lineage":["https://openalex.org/I134161618"]}],"countries":["TW"],"is_corresponding":true,"raw_author_name":"You-Lin Tsai","raw_affiliation_strings":["National Taiwan Normal University,Department of Electrical Engineering","Department of Electrical Engineering, National Taiwan Normal University"],"affiliations":[{"raw_affiliation_string":"National Taiwan Normal University,Department of Electrical Engineering","institution_ids":["https://openalex.org/I134161618"]},{"raw_affiliation_string":"Department of Electrical Engineering, National Taiwan Normal University","institution_ids":["https://openalex.org/I134161618"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011289357","display_name":"Cheng-Hung Lin","orcid":"https://orcid.org/0000-0003-0044-3840"},"institutions":[{"id":"https://openalex.org/I134161618","display_name":"National Taiwan Normal University","ror":"https://ror.org/059dkdx38","country_code":"TW","type":"education","lineage":["https://openalex.org/I134161618"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Cheng-Hung Lin","raw_affiliation_strings":["National Taiwan Normal University,Department of Electrical Engineering","Department of Electrical Engineering, National Taiwan Normal University"],"affiliations":[{"raw_affiliation_string":"National Taiwan Normal University,Department of Electrical Engineering","institution_ids":["https://openalex.org/I134161618"]},{"raw_affiliation_string":"Department of Electrical Engineering, National Taiwan Normal University","institution_ids":["https://openalex.org/I134161618"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5021001528","display_name":"Po\u2010Yung Chou","orcid":null},"institutions":[{"id":"https://openalex.org/I134161618","display_name":"National Taiwan Normal University","ror":"https://ror.org/059dkdx38","country_code":"TW","type":"education","lineage":["https://openalex.org/I134161618"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Po-Yung Chou","raw_affiliation_strings":["National Taiwan Normal University,Department of Electrical Engineering","Department of Electrical Engineering, National Taiwan Normal University"],"affiliations":[{"raw_affiliation_string":"National Taiwan Normal University,Department of Electrical Engineering","institution_ids":["https://openalex.org/I134161618"]},{"raw_affiliation_string":"Department of Electrical Engineering, National Taiwan Normal University","institution_ids":["https://openalex.org/I134161618"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5101310720"],"corresponding_institution_ids":["https://openalex.org/I134161618"],"apc_list":null,"apc_paid":null,"fwci":0.5248,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.61085995,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9987999796867371,"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":0.9987999796867371,"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":0.996999979019165,"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"}},{"id":"https://openalex.org/T11438","display_name":"Retinal Imaging and Analysis","score":0.9954000115394592,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/distillation","display_name":"Distillation","score":0.7426337599754333},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7144654393196106},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5536403059959412},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.38957011699676514},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.35029464960098267},{"id":"https://openalex.org/keywords/chromatography","display_name":"Chromatography","score":0.09864494204521179},{"id":"https://openalex.org/keywords/chemistry","display_name":"Chemistry","score":0.0874115526676178}],"concepts":[{"id":"https://openalex.org/C204030448","wikidata":"https://www.wikidata.org/wiki/Q101017","display_name":"Distillation","level":2,"score":0.7426337599754333},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7144654393196106},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5536403059959412},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.38957011699676514},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.35029464960098267},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.09864494204521179},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0874115526676178}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icce59016.2024.10444242","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icce59016.2024.10444242","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Consumer Electronics (ICCE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5899999737739563,"id":"https://metadata.un.org/sdg/2","display_name":"Zero hunger"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W1677182931","https://openalex.org/W1690739335","https://openalex.org/W2295107390","https://openalex.org/W2407386500","https://openalex.org/W2737725206","https://openalex.org/W2739879705","https://openalex.org/W2773003563","https://openalex.org/W2950557962","https://openalex.org/W3009073662","https://openalex.org/W6637551013"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W3046775127","https://openalex.org/W4394896187","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W3107602296","https://openalex.org/W4364306694","https://openalex.org/W4312192474","https://openalex.org/W2033914206"],"abstract_inverted_index":{"The":[0,43],"current":[1],"state-of-the-art":[2],"network":[3],"models":[4],"have":[5],"achieved":[6,263],"remarkable":[7],"performance.":[8,214],"However,":[9],"they":[10],"often":[11],"face":[12],"an":[13,145],"issue":[14],"of":[15,45,80,89,157,250],"having":[16],"excessively":[17],"large":[18],"architectures,":[19],"making":[20],"them":[21],"challenging":[22],"to":[23,30,56,160,176,191,211,254],"deploy":[24],"on":[25,102,186],"edge":[26],"devices.":[27],"In":[28,97,189,215],"response":[29],"this":[31,74,95,98,112,149,195],"challenge,":[32],"a":[33,52,57,125,170,246,264],"groundbreaking":[34],"solution":[35],"known":[36],"as":[37,162,169],"knowledge":[38,46,103,269],"distillation":[39,47,90,104,193,270],"has":[40,68,85],"been":[41,86],"introduced.":[42],"concept":[44],"involves":[48],"transferring":[49],"information":[50],"from":[51,179],"complex":[53,126],"teacher":[54,181],"model":[55,127,175,210],"simpler":[58],"student":[59,174,209,258],"model,":[60],"effectively":[61,177],"reducing":[62],"the":[63,78,117,173,180,208,220,226,239,255],"model\u2019s":[64,182],"complexity.":[65],"Prior":[66],"approach":[67,262],"demonstrated":[69,245],"promising":[70],"transfer":[71],"effects":[72],"through":[73],"technique.":[75],"Nevertheless,":[76],"in":[77],"field":[79],"fine-grained":[81,108,201],"image":[82,109],"classification,":[83],"there":[84],"limited":[87],"exploration":[88],"methods":[91],"custom-tailored":[92],"specifically":[93,105],"for":[94,107,148,200],"domain.":[96],"paper,":[99],"we":[100,143,218],"focus":[101],"designed":[106],"recognition.":[110],"Notably,":[111],"strategy":[113,147,196],"is":[114,138],"inspired":[115],"by":[116],"Class":[118],"Activation":[119],"Maps":[120],"(CAM).":[121],"We":[122,235],"first":[123],"train":[124],"and":[128,184,206,231,242],"use":[129],"it":[130,161,168],"generated":[131],"feature":[132,233],"maps":[133,222],"with":[134],"spatial":[135],"information,":[136],"which":[137,152],"call":[139],"hint":[140,150,221],"maps.":[141],"Furthermore,":[142],"propose":[144],"adjustment":[146],"map,":[151],"can":[153],"control":[154],"local":[155],"distribution":[156],"information.":[158],"Referring":[159],"Controllable":[163],"Size":[164],"CAM":[165],"(CTRLS-CAM).":[166],"Use":[167],"guide":[171],"allowing":[172],"learn":[178],"behavior":[183],"concentrate":[185],"discriminate":[187],"details.":[188],"contrast":[190],"conventional":[192],"models,":[194],"proves":[197],"particularly":[198],"advantageous":[199],"recognition,":[202],"enhancing":[203],"learning":[204],"outcomes":[205],"enabling":[207],"achieve":[212],"superior":[213],"CTRLS-CAM":[216],"method,":[217],"refine":[219],"value":[223],"distribution,":[224],"redefining":[225],"relative":[227],"relationships":[228],"between":[229],"primary":[230],"secondary":[232],"areas.":[234],"conducted":[236],"experiments":[237],"using":[238],"CUB200-2011":[240],"dataset,":[241],"our":[243,261],"results":[244],"significant":[247],"accuracy":[248],"improvement":[249],"about":[251],"5%":[252],"compared":[253],"original":[256],"non-distilled":[257],"model.":[259],"Moreover,":[260],"1.23%":[265],"enhancement":[266],"over":[267],"traditional":[268],"methods.":[271]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}