{"id":"https://openalex.org/W4410867409","doi":"https://doi.org/10.32604/cmc.2025.063109","title":"Implicit Feature Contrastive Learning for Few-Shot Object Detection","display_name":"Implicit Feature Contrastive Learning for Few-Shot Object Detection","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4410867409","doi":"https://doi.org/10.32604/cmc.2025.063109"},"language":"en","primary_location":{"id":"doi:10.32604/cmc.2025.063109","is_oa":true,"landing_page_url":"https://doi.org/10.32604/cmc.2025.063109","pdf_url":null,"source":{"id":"https://openalex.org/S4210191605","display_name":"Computers, materials & continua/Computers, materials & continua (Print)","issn_l":"1546-2218","issn":["1546-2218","1546-2226"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computers, Materials & Continua","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://doi.org/10.32604/cmc.2025.063109","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5018012012","display_name":"Gang Li","orcid":"https://orcid.org/0000-0002-8573-1608"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Gang Li","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100459154","display_name":"Zheng Zhou","orcid":"https://orcid.org/0000-0002-9084-5378"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zheng Zhou","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100354683","display_name":"Yang Zhang","orcid":"https://orcid.org/0000-0002-4170-4798"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang Zhang","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044238570","display_name":"Chuanyun Xu","orcid":"https://orcid.org/0000-0002-1609-7658"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chuanyun Xu","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Zihan Ruan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zihan Ruan","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103089819","display_name":"Pengfei Lv","orcid":"https://orcid.org/0000-0002-0523-9198"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pengfei Lv","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103084861","display_name":"Ru Wang","orcid":"https://orcid.org/0009-0003-0242-3701"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ru Wang","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110699311","display_name":"Xinyu Fan","orcid":"https://orcid.org/0009-0002-4974-8303"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xinyu Fan","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5063425380","display_name":"Wei Tan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wei Tan","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":9,"corresponding_author_ids":["https://openalex.org/A5018012012"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0543779,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"84","issue":"1","first_page":"1615","last_page":"1632"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9923999905586243,"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"}},"topics":[{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9923999905586243,"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/T12676","display_name":"Machine Learning and ELM","score":0.9817000031471252,"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/T12597","display_name":"Fire Detection and Safety Systems","score":0.9509999752044678,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6717206239700317},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.61262047290802},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5980682969093323},{"id":"https://openalex.org/keywords/shot","display_name":"Shot (pellet)","score":0.5646637678146362},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.5017070770263672},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.42648977041244507},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.42183324694633484},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.36050334572792053},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.32622218132019043},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.18367999792099},{"id":"https://openalex.org/keywords/chemistry","display_name":"Chemistry","score":0.07532209157943726}],"concepts":[{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6717206239700317},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.61262047290802},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5980682969093323},{"id":"https://openalex.org/C2778344882","wikidata":"https://www.wikidata.org/wiki/Q278938","display_name":"Shot (pellet)","level":2,"score":0.5646637678146362},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5017070770263672},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.42648977041244507},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.42183324694633484},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.36050334572792053},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.32622218132019043},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.18367999792099},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.07532209157943726},{"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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.32604/cmc.2025.063109","is_oa":true,"landing_page_url":"https://doi.org/10.32604/cmc.2025.063109","pdf_url":null,"source":{"id":"https://openalex.org/S4210191605","display_name":"Computers, materials & continua/Computers, materials & continua (Print)","issn_l":"1546-2218","issn":["1546-2218","1546-2226"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computers, Materials & Continua","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.32604/cmc.2025.063109","is_oa":true,"landing_page_url":"https://doi.org/10.32604/cmc.2025.063109","pdf_url":null,"source":{"id":"https://openalex.org/S4210191605","display_name":"Computers, materials & continua/Computers, materials & continua (Print)","issn_l":"1546-2218","issn":["1546-2218","1546-2226"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computers, Materials & Continua","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W2031489346","https://openalex.org/W2117539524","https://openalex.org/W2894906112","https://openalex.org/W4211090899","https://openalex.org/W4285098584","https://openalex.org/W4366083832","https://openalex.org/W4400648075"],"related_works":["https://openalex.org/W2074502265","https://openalex.org/W4214877189","https://openalex.org/W2773965352","https://openalex.org/W2381179799","https://openalex.org/W2980279061","https://openalex.org/W2334685461","https://openalex.org/W2366718574","https://openalex.org/W2359774528","https://openalex.org/W4292830139","https://openalex.org/W4319309705"],"abstract_inverted_index":{"Although":[0],"conventional":[1],"object":[2,26,53,142],"detection":[3,27,54],"methods":[4],"achieve":[5],"high":[6],"accuracy":[7],"through":[8],"extensively":[9],"annotated":[10,45],"datasets,":[11],"acquiring":[12],"such":[13],"large-scale":[14],"labeled":[15],"data":[16],"remains":[17],"challenging":[18],"and":[19,37,91,112,134,144,163],"cost-prohibitive":[20],"in":[21,40,51,56,107],"numerous":[22],"real-world":[23],"applications.":[24],"Few-shot":[25],"presents":[28],"a":[29,108,157],"new":[30],"research":[31],"idea":[32],"that":[33,153],"aims":[34],"to":[35,61,87,172],"localize":[36],"classify":[38],"objects":[39],"images":[41],"using":[42],"only":[43],"limited":[44],"examples.":[46],"However,":[47],"the":[48,57,64,140,173],"inherent":[49],"challenge":[50],"few-shot":[52],"lies":[55],"insufficient":[58],"sample":[59,65,105],"diversity":[60,94],"fully":[62],"characterize":[63],"feature":[66,93,110,132,136],"distribution,":[67],"which":[68],"consequently":[69],"impacts":[70],"model":[71,175],"performance.":[72],"Inspired":[73],"by":[74],"contrastive":[75],"learning":[76,128],"principles,":[77],"we":[78],"propose":[79],"an":[80],"Implicit":[81],"Feature":[82],"Contrastive":[83],"Learning":[84],"(IFCL)":[85],"module":[86,101],"address":[88],"this":[89],"limitation":[90],"augment":[92],"for":[95],"more":[96,126],"robust":[97],"representational":[98],"learning.":[99],"This":[100,123],"generates":[102],"augmented":[103],"support":[104],"features":[106],"mixed":[109],"space":[111],"implicitly":[113],"contrasts":[114],"them":[115],"with":[116],"query":[117],"Region":[118],"of":[119,129,160,167],"Interest":[120],"(RoI)":[121],"features.":[122],"approach":[124],"facilitates":[125],"comprehensive":[127],"both":[130],"intra-class":[131],"similarity":[133],"inter-class":[135],"diversity,":[137],"thereby":[138],"enhancing":[139],"model\u2019s":[141],"classification":[143],"localization":[145],"capabilities.":[146],"Extensive":[147],"experiments":[148],"on":[149,165],"PASCAL":[150],"VOC":[151],"show":[152],"our":[154],"method":[155],"achieves":[156],"respective":[158],"improvement":[159],"3.2%,":[161],"1.8%,":[162],"2.3%":[164],"10-shot":[166],"three":[168],"Novel":[169],"Sets":[170],"compared":[171],"baseline":[174],"FPD.":[176]},"counts_by_year":[],"updated_date":"2026-04-17T18:11:37.981687","created_date":"2025-10-10T00:00:00"}