{"id":"https://openalex.org/W7137933460","doi":"https://doi.org/10.1016/j.patrec.2026.03.014","title":"Prototype distance ratio sampling for generalised few shot object detection","display_name":"Prototype distance ratio sampling for generalised few shot object detection","publication_year":2026,"publication_date":"2026-03-17","ids":{"openalex":"https://openalex.org/W7137933460","doi":"https://doi.org/10.1016/j.patrec.2026.03.014"},"language":"en","primary_location":{"id":"doi:10.1016/j.patrec.2026.03.014","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.patrec.2026.03.014","pdf_url":null,"source":{"id":"https://openalex.org/S151820558","display_name":"Pattern Recognition Letters","issn_l":"0167-8655","issn":["0167-8655","1872-7344"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Pattern Recognition Letters","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1016/j.patrec.2026.03.014","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5129708344","display_name":"Alessandro Lekkas","orcid":null},"institutions":[{"id":"https://openalex.org/I181647926","display_name":"University of Strathclyde","ror":"https://ror.org/00n3w3b69","country_code":"GB","type":"education","lineage":["https://openalex.org/I181647926"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Alessandro Lekkas","raw_affiliation_strings":["Computer and Information Sciences, University of Strathclyde, 16 Richmond Street, Glasgow, G1 1XQ, Scotland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer and Information Sciences, University of Strathclyde, 16 Richmond Street, Glasgow, G1 1XQ, Scotland","institution_ids":["https://openalex.org/I181647926"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129693751","display_name":"Marc Roper","orcid":null},"institutions":[{"id":"https://openalex.org/I181647926","display_name":"University of Strathclyde","ror":"https://ror.org/00n3w3b69","country_code":"GB","type":"education","lineage":["https://openalex.org/I181647926"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Marc Roper","raw_affiliation_strings":["Computer and Information Sciences, University of Strathclyde, 16 Richmond Street, Glasgow, G1 1XQ, Scotland"],"raw_orcid":"https://orcid.org/0000-0001-6794-4637","affiliations":[{"raw_affiliation_string":"Computer and Information Sciences, University of Strathclyde, 16 Richmond Street, Glasgow, G1 1XQ, Scotland","institution_ids":["https://openalex.org/I181647926"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5004036080","display_name":"Andrew Abel","orcid":"https://orcid.org/0000-0002-3631-8753"},"institutions":[{"id":"https://openalex.org/I181647926","display_name":"University of Strathclyde","ror":"https://ror.org/00n3w3b69","country_code":"GB","type":"education","lineage":["https://openalex.org/I181647926"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Andrew Abel","raw_affiliation_strings":["Computer and Information Sciences, University of Strathclyde, 16 Richmond Street, Glasgow, G1 1XQ, Scotland"],"raw_orcid":"https://orcid.org/0000-0002-3631-8753","affiliations":[{"raw_affiliation_string":"Computer and Information Sciences, University of Strathclyde, 16 Richmond Street, Glasgow, G1 1XQ, Scotland","institution_ids":["https://openalex.org/I181647926"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5004036080"],"corresponding_institution_ids":["https://openalex.org/I181647926"],"apc_list":{"value":2500,"currency":"USD","value_usd":2500},"apc_paid":{"value":2500,"currency":"USD","value_usd":2500},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.26222974,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"204","issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.11110000312328339,"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":0.11110000312328339,"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":0.0820000022649765,"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/T11398","display_name":"Hand Gesture Recognition Systems","score":0.06669999659061432,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"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/object-detection","display_name":"Object detection","score":0.6061000227928162},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.48809999227523804},{"id":"https://openalex.org/keywords/shot","display_name":"Shot (pellet)","score":0.47440001368522644},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.4287000000476837},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.41339999437332153},{"id":"https://openalex.org/keywords/one-shot","display_name":"One shot","score":0.3303000032901764},{"id":"https://openalex.org/keywords/single-shot","display_name":"Single shot","score":0.31839999556541443}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6552000045776367},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6481000185012817},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6172000169754028},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.6061000227928162},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.48809999227523804},{"id":"https://openalex.org/C2778344882","wikidata":"https://www.wikidata.org/wiki/Q278938","display_name":"Shot (pellet)","level":2,"score":0.47440001368522644},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.4287000000476837},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.41339999437332153},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3402000069618225},{"id":"https://openalex.org/C2992734406","wikidata":"https://www.wikidata.org/wiki/Q413267","display_name":"One shot","level":2,"score":0.3303000032901764},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3228999972343445},{"id":"https://openalex.org/C3019835501","wikidata":"https://www.wikidata.org/wiki/Q1310130","display_name":"Single shot","level":2,"score":0.31839999556541443},{"id":"https://openalex.org/C193536780","wikidata":"https://www.wikidata.org/wiki/Q1513153","display_name":"Edge detection","level":4,"score":0.31540000438690186},{"id":"https://openalex.org/C71681937","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object-class detection","level":5,"score":0.2879999876022339},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.2870999872684479},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.2711000144481659},{"id":"https://openalex.org/C203595873","wikidata":"https://www.wikidata.org/wiki/Q25389927","display_name":"Change detection","level":2,"score":0.26969999074935913},{"id":"https://openalex.org/C137270730","wikidata":"https://www.wikidata.org/wiki/Q120811","display_name":"Detection theory","level":3,"score":0.258899986743927}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1016/j.patrec.2026.03.014","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.patrec.2026.03.014","pdf_url":null,"source":{"id":"https://openalex.org/S151820558","display_name":"Pattern Recognition Letters","issn_l":"0167-8655","issn":["0167-8655","1872-7344"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Pattern Recognition Letters","raw_type":"journal-article"},{"id":"pmh:oai:strathprints.strath.ac.uk:95817","is_oa":true,"landing_page_url":"https://strathprints.strath.ac.uk/view/author/1298603.html>","pdf_url":"https://strathprints.strath.ac.uk/95817/7/Lekkas-etal-PRL-2026-Prototype-distance-ratio-sampling.pdf","source":{"id":"https://openalex.org/S4306402226","display_name":"Strathprints: The University of Strathclyde institutional repository (University of Strathclyde)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I181647926","host_organization_name":"University of Strathclyde","host_organization_lineage":["https://openalex.org/I181647926"],"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":"Article"}],"best_oa_location":{"id":"doi:10.1016/j.patrec.2026.03.014","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.patrec.2026.03.014","pdf_url":null,"source":{"id":"https://openalex.org/S151820558","display_name":"Pattern Recognition Letters","issn_l":"0167-8655","issn":["0167-8655","1872-7344"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Pattern Recognition Letters","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":6,"referenced_works":["https://openalex.org/W2060277733","https://openalex.org/W2108598243","https://openalex.org/W2143668817","https://openalex.org/W3111759753","https://openalex.org/W4312210066","https://openalex.org/W4391899597"],"related_works":[],"abstract_inverted_index":{"Few-Shot":[0,18,59],"Learning":[1,34,65],"has":[2,22],"emerged":[3],"as":[4],"a":[5,20,40,116,137],"topic":[6],"that":[7,84,166],"maximises":[8],"DNN":[9],"performance":[10,43,104],"based":[11],"on":[12,44,68,154,157,170],"very":[13],"few":[14],"samples.":[15],"In":[16,48],"Generalised":[17,58],"Learning,":[19],"model":[21],"to":[23,39,89,136],"learn":[24],"new":[25,36],"few-shot":[26],"classes":[27,37],"while":[28],"recalling":[29],"earlier":[30],"large-scale":[31],"training":[32],"classes.":[33],"the":[35,45,55,106,120,124,128,158,171],"leads":[38],"drop":[41],"in":[42,71],"base":[46,125],"ones.":[47],"this":[49],"work,":[50],"we":[51,82,164],"identify":[52],"and":[53,63,76,96,127,160,174],"explore":[54],"parallels":[56],"between":[57],"Object":[60],"Detection":[61],"(G-FSOD)":[62],"Continual":[64],"(CL),":[66],"focusing":[67],"two":[69],"areas":[70],"particular:":[72],"gradient":[73,85],"manipulation":[74,86],"methods":[75,87],"sampling":[77,113,177],"strategies.":[78,178],"Through":[79],"extensive":[80],"experimentation":[81],"demonstrate":[83],"appear":[88],"be":[90],"no":[91],"better":[92],"than":[93],"existing":[94],"techniques":[95],"do":[97],"not":[98],"improve":[99],"performance,":[100],"but":[101],"actually":[102],"harm":[103],"unless":[105],"gradients":[107],"are":[108],"averaged.":[109],"Our":[110,143],"investigations":[111],"into":[112,145,151],"strategies":[114],"consider":[115],"number":[117],"of":[118,122,130],"aspects:":[119],"impact":[121,153],"removing":[123],"limit":[126],"effectiveness":[129],"different":[131],"distance":[132],"measures":[133],"(with":[134],"respect":[135],"class":[138],"prototype)":[139],"for":[140],"sample":[141],"selection.":[142],"experiments":[144],"these":[146],"aspects":[147],"reveal":[148],"illuminating":[149],"insights":[150],"their":[152],"Average":[155],"Precision":[156],"COCO":[159],"VOC":[161],"datasets.":[162],"Consequently,":[163],"suggest":[165],"G-FSOD":[167],"research":[168],"focus":[169],"replay":[172],"aspect":[173],"investigate":[175],"other":[176]},"counts_by_year":[],"updated_date":"2026-06-14T06:11:07.267592","created_date":"2026-03-18T00:00:00"}
