{"id":"https://openalex.org/W4390481791","doi":"https://doi.org/10.1109/ssci52147.2023.10371859","title":"Symmetric Fine-Tuning for Improving Few-Shot Object Detection","display_name":"Symmetric Fine-Tuning for Improving Few-Shot Object Detection","publication_year":2023,"publication_date":"2023-12-05","ids":{"openalex":"https://openalex.org/W4390481791","doi":"https://doi.org/10.1109/ssci52147.2023.10371859"},"language":"en","primary_location":{"id":"doi:10.1109/ssci52147.2023.10371859","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ssci52147.2023.10371859","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE Symposium Series on Computational Intelligence (SSCI)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5055793446","display_name":"Emmanouil Mpampis","orcid":null},"institutions":[{"id":"https://openalex.org/I21370196","display_name":"Aristotle University of Thessaloniki","ror":"https://ror.org/02j61yw88","country_code":"GR","type":"education","lineage":["https://openalex.org/I21370196"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Emmanouil Mpampis","raw_affiliation_strings":["Aristotle University of Thessaloniki,Computational Intelligence and Deep Learning Group, AlIA Lab.,Department of Informatics,Thessaloniki,Greece","Department of Informatics, Computational Intelligence and Deep Learning Group, AlIA Lab., Aristotle University of Thessaloniki, Thessaloniki, Greece"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Aristotle University of Thessaloniki,Computational Intelligence and Deep Learning Group, AlIA Lab.,Department of Informatics,Thessaloniki,Greece","institution_ids":["https://openalex.org/I21370196"]},{"raw_affiliation_string":"Department of Informatics, Computational Intelligence and Deep Learning Group, AlIA Lab., Aristotle University of Thessaloniki, Thessaloniki, Greece","institution_ids":["https://openalex.org/I21370196"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061050264","display_name":"Nikolaos Passalis","orcid":"https://orcid.org/0000-0003-1177-9139"},"institutions":[{"id":"https://openalex.org/I21370196","display_name":"Aristotle University of Thessaloniki","ror":"https://ror.org/02j61yw88","country_code":"GR","type":"education","lineage":["https://openalex.org/I21370196"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Nikolaos Passalis","raw_affiliation_strings":["Aristotle University of Thessaloniki,Computational Intelligence and Deep Learning Group, AlIA Lab.,Department of Informatics,Thessaloniki,Greece","Department of Informatics, Computational Intelligence and Deep Learning Group, AlIA Lab., Aristotle University of Thessaloniki, Thessaloniki, Greece"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Aristotle University of Thessaloniki,Computational Intelligence and Deep Learning Group, AlIA Lab.,Department of Informatics,Thessaloniki,Greece","institution_ids":["https://openalex.org/I21370196"]},{"raw_affiliation_string":"Department of Informatics, Computational Intelligence and Deep Learning Group, AlIA Lab., Aristotle University of Thessaloniki, Thessaloniki, Greece","institution_ids":["https://openalex.org/I21370196"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5041054091","display_name":"Anastasios Tefas","orcid":"https://orcid.org/0000-0003-1288-3667"},"institutions":[{"id":"https://openalex.org/I21370196","display_name":"Aristotle University of Thessaloniki","ror":"https://ror.org/02j61yw88","country_code":"GR","type":"education","lineage":["https://openalex.org/I21370196"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Anastasios Tefas","raw_affiliation_strings":["Aristotle University of Thessaloniki,Computational Intelligence and Deep Learning Group, AlIA Lab.,Department of Informatics,Thessaloniki,Greece","Department of Informatics, Computational Intelligence and Deep Learning Group, AlIA Lab., Aristotle University of Thessaloniki, Thessaloniki, Greece"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Aristotle University of Thessaloniki,Computational Intelligence and Deep Learning Group, AlIA Lab.,Department of Informatics,Thessaloniki,Greece","institution_ids":["https://openalex.org/I21370196"]},{"raw_affiliation_string":"Department of Informatics, Computational Intelligence and Deep Learning Group, AlIA Lab., Aristotle University of Thessaloniki, Thessaloniki, Greece","institution_ids":["https://openalex.org/I21370196"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I21370196"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"598","last_page":"602"},"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9994000196456909,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9954000115394592,"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/overfitting","display_name":"Overfitting","score":0.8844605684280396},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.788445234298706},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7807890176773071},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.6492926478385925},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.598991334438324},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5436155200004578},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.539271354675293},{"id":"https://openalex.org/keywords/shot","display_name":"Shot (pellet)","score":0.5161052942276001},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5087328553199768},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.48976874351501465},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.4873107671737671},{"id":"https://openalex.org/keywords/limit","display_name":"Limit (mathematics)","score":0.48451703786849976},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4533814489841461},{"id":"https://openalex.org/keywords/single-shot","display_name":"Single shot","score":0.43090376257896423},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.41555628180503845},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.39509522914886475},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3484615087509155},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3434686064720154},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.13004547357559204},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.0943865180015564}],"concepts":[{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.8844605684280396},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.788445234298706},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7807890176773071},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.6492926478385925},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.598991334438324},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5436155200004578},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.539271354675293},{"id":"https://openalex.org/C2778344882","wikidata":"https://www.wikidata.org/wiki/Q278938","display_name":"Shot (pellet)","level":2,"score":0.5161052942276001},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5087328553199768},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.48976874351501465},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.4873107671737671},{"id":"https://openalex.org/C151201525","wikidata":"https://www.wikidata.org/wiki/Q177239","display_name":"Limit (mathematics)","level":2,"score":0.48451703786849976},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4533814489841461},{"id":"https://openalex.org/C3019835501","wikidata":"https://www.wikidata.org/wiki/Q1310130","display_name":"Single shot","level":2,"score":0.43090376257896423},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.41555628180503845},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.39509522914886475},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3484615087509155},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3434686064720154},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.13004547357559204},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0943865180015564},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"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/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ssci52147.2023.10371859","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ssci52147.2023.10371859","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE Symposium Series on Computational Intelligence (SSCI)","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":24,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1861492603","https://openalex.org/W2031489346","https://openalex.org/W2193145675","https://openalex.org/W2963012557","https://openalex.org/W2964184826","https://openalex.org/W2989604896","https://openalex.org/W2996583130","https://openalex.org/W3034942609","https://openalex.org/W3035163969","https://openalex.org/W3106250896","https://openalex.org/W3132757466","https://openalex.org/W3134307371","https://openalex.org/W3200297852","https://openalex.org/W4288083516","https://openalex.org/W4292787476","https://openalex.org/W4293584584","https://openalex.org/W4294975662","https://openalex.org/W4312303251","https://openalex.org/W4312702383","https://openalex.org/W4366083832","https://openalex.org/W6750227808","https://openalex.org/W6752488411","https://openalex.org/W6791141078"],"related_works":["https://openalex.org/W3142396426","https://openalex.org/W2471333042","https://openalex.org/W4396643691","https://openalex.org/W4402383816","https://openalex.org/W2955491601","https://openalex.org/W3011512764","https://openalex.org/W146529714","https://openalex.org/W4402559869","https://openalex.org/W2316500695","https://openalex.org/W2017914143"],"abstract_inverted_index":{"Object":[0],"detection":[1,62,72,135,186],"plays":[2],"a":[3,50,81,100,172,191],"crucial":[4],"role":[5],"in":[6,96,111,153,160],"automated":[7],"image":[8],"analysis":[9],"by":[10],"identifying":[11],"and":[12,125,181,207,212],"localizing":[13],"objects":[14],"within":[15],"an":[16],"image.":[17],"One-stage":[18],"Deep":[19],"Learning":[20],"(DL)-based":[21],"object":[22,61,87,108],"detectors":[23],"have":[24,64],"achieved":[25],"impressive":[26],"results,":[27],"primarily":[28],"due":[29],"to":[30,105,127,189],"large-scale":[31],"datasets":[32],"available":[33],"for":[34,85,140,200],"training":[35],"them.":[36],"However,":[37,110],"these":[38],"approaches":[39,63],"rely":[40],"heavily":[41],"on":[42],"abundant":[43],"labeled":[44],"data,":[45],"posing":[46],"challenges":[47],"when":[48],"only":[49,118],"few":[51],"samples":[52,104],"per":[53],"class":[54],"are":[55,137],"available.":[56],"To":[57,166],"this":[58,112,164,168,210],"end,":[59],"few-shot":[60,86],"been":[65],"proposed.":[66],"Among":[67],"them,":[68],"fine-tuning":[69,117,174],"the":[70,76,97,119,130,134,141,179,185,205],"final":[71],"head":[73,136],"while":[74,196],"keeping":[75],"feature":[77],"extractor/backbone":[78],"frozen":[79],"is":[80],"commonly":[82],"used":[83],"approach":[84,90,211],"detection.":[88],"This":[89],"effectively":[91],"utilizes":[92],"pre-existing":[93],"knowledge":[94],"encoded":[95],"backbone,":[98],"using":[99],"small":[101],"number":[102],"of":[103,133,184,209],"learn":[106],"new":[107,142],"categories.":[109],"paper,":[113],"we":[114,170],"argue":[115],"that":[116,150,176],"last":[120,182],"layers":[121,132,156,183],"may":[122],"limit":[123],"accuracy":[124],"lead":[126],"overfitting":[128],"if":[129],"initial":[131],"not":[138],"adapted":[139],"task.":[143],"The":[144],"data":[145],"processing":[146],"inequality,":[147],"which":[148],"states":[149],"information":[151],"lost":[152],"early":[154],"network":[155],"cannot":[157],"be":[158],"recovered":[159],"subsequent":[161],"ones,":[162],"supports":[163],"argument.":[165],"address":[167],"issue,":[169],"propose":[171],"symmetric":[173],"method":[175],"involves":[177],"both":[178],"first":[180],"head,":[187],"aiming":[188],"maintain":[190],"fixed":[192],"trainable":[193],"parameter":[194],"budget":[195],"strategically":[197],"selecting":[198],"parameters":[199],"fine-tuning.":[201],"Experimental":[202],"results":[203],"demonstrate":[204],"effectiveness":[206],"efficiency":[208],"open":[213],"up":[214],"several":[215],"interesting":[216],"future":[217],"research":[218],"directions.":[219]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
