{"id":"https://openalex.org/W4206421627","doi":"https://doi.org/10.1109/m2vip49856.2021.9665036","title":"On-the-fly Learning of New Objects and Instances","display_name":"On-the-fly Learning of New Objects and Instances","publication_year":2021,"publication_date":"2021-11-26","ids":{"openalex":"https://openalex.org/W4206421627","doi":"https://doi.org/10.1109/m2vip49856.2021.9665036"},"language":"en","primary_location":{"id":"doi:10.1109/m2vip49856.2021.9665036","is_oa":false,"landing_page_url":"https://doi.org/10.1109/m2vip49856.2021.9665036","pdf_url":null,"source":{"id":"https://openalex.org/S4363608277","display_name":"2021 27th International Conference on Mechatronics and Machine Vision in Practice (M2VIP)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 27th International Conference on Mechatronics and Machine Vision in Practice (M2VIP)","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/A5027904523","display_name":"Ping Guo","orcid":"https://orcid.org/0000-0003-3495-688X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ping Guo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100414840","display_name":"Zhigang Wang","orcid":"https://orcid.org/0000-0002-7123-335X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhigang Wang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015256862","display_name":"Hua Yang","orcid":"https://orcid.org/0000-0002-9796-5663"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hua Yang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047341502","display_name":"Xuesong Shi","orcid":"https://orcid.org/0000-0002-3880-4501"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xuesong Shi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5100391587","display_name":"Yimin Zhang","orcid":"https://orcid.org/0000-0001-7673-8800"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yimin Zhang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.20055453,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"114","issue":null,"first_page":"375","last_page":"380"},"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":0.9994000196456909,"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"}},"topics":[{"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/T10036","display_name":"Advanced Neural Network Applications","score":0.996999979019165,"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":0.9955999851226807,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7947571873664856},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.6635948419570923},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6055263876914978},{"id":"https://openalex.org/keywords/software-deployment","display_name":"Software deployment","score":0.5919704437255859},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.5396258234977722},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.5279892086982727},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.5088956356048584},{"id":"https://openalex.org/keywords/dependency","display_name":"Dependency (UML)","score":0.4838348925113678},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.4557473659515381},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4496486783027649},{"id":"https://openalex.org/keywords/on-the-fly","display_name":"On the fly","score":0.4428287446498871},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.425339013338089},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.19895437359809875},{"id":"https://openalex.org/keywords/software-engineering","display_name":"Software engineering","score":0.1204652488231659},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.11302542686462402}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7947571873664856},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.6635948419570923},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6055263876914978},{"id":"https://openalex.org/C105339364","wikidata":"https://www.wikidata.org/wiki/Q2297740","display_name":"Software deployment","level":2,"score":0.5919704437255859},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.5396258234977722},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.5279892086982727},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.5088956356048584},{"id":"https://openalex.org/C19768560","wikidata":"https://www.wikidata.org/wiki/Q320727","display_name":"Dependency (UML)","level":2,"score":0.4838348925113678},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.4557473659515381},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4496486783027649},{"id":"https://openalex.org/C2781020372","wikidata":"https://www.wikidata.org/wiki/Q533093","display_name":"On the fly","level":2,"score":0.4428287446498871},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.425339013338089},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.19895437359809875},{"id":"https://openalex.org/C115903868","wikidata":"https://www.wikidata.org/wiki/Q80993","display_name":"Software engineering","level":1,"score":0.1204652488231659},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.11302542686462402},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/m2vip49856.2021.9665036","is_oa":false,"landing_page_url":"https://doi.org/10.1109/m2vip49856.2021.9665036","pdf_url":null,"source":{"id":"https://openalex.org/S4363608277","display_name":"2021 27th International Conference on Mechatronics and Machine Vision in Practice (M2VIP)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 27th International Conference on Mechatronics and Machine Vision in Practice (M2VIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W1861492603","https://openalex.org/W1999689402","https://openalex.org/W2001485836","https://openalex.org/W2133324800","https://openalex.org/W2473930607","https://openalex.org/W2560647685","https://openalex.org/W2962707369","https://openalex.org/W2962804657","https://openalex.org/W2963112696","https://openalex.org/W2963227409","https://openalex.org/W2963311506","https://openalex.org/W2963540014","https://openalex.org/W2964189064","https://openalex.org/W2968409168","https://openalex.org/W2989706229","https://openalex.org/W3012362498","https://openalex.org/W3013325675","https://openalex.org/W3089740767","https://openalex.org/W3117549273","https://openalex.org/W6639102338","https://openalex.org/W6730146409","https://openalex.org/W6735467293","https://openalex.org/W6737514476","https://openalex.org/W6742852309","https://openalex.org/W6760424586","https://openalex.org/W6787559691"],"related_works":["https://openalex.org/W2770234245","https://openalex.org/W96612179","https://openalex.org/W4229499248","https://openalex.org/W2566006169","https://openalex.org/W1567818861","https://openalex.org/W2987774938","https://openalex.org/W4390608645","https://openalex.org/W4256492088","https://openalex.org/W632915154","https://openalex.org/W2055733372"],"abstract_inverted_index":{"This":[0,90],"paper":[1,91],"focus":[2],"on":[3,106,180],"efficient":[4],"learning":[5],"of":[6,100,171],"new":[7,25,75,95,118,125],"objects":[8,26,56,76,96],"by":[9,132],"robots,":[10,53],"at":[11],"both":[12],"instance":[13,119],"level":[14],"and":[15,37,60,62,123],"class":[16,126],"level.":[17],"Despite":[18],"the":[19,33,38,54,87,101,104,161,169],"great":[20],"achievements":[21],"in":[22,46,51,86,120,127],"deep":[23],"learning,":[24,138,140],"are":[27,43,83,165],"not":[28,44,84],"well":[29],"handled":[30],"due":[31],"to":[32,66,80,93,115,129,167,186],"big":[34,68,108],"data":[35,69],"dependency":[36,105],"closed":[39],"set":[40],"assumption,":[41],"which":[42],"satisfied":[45],"many":[47],"applications.":[48],"For":[49],"example,":[50],"service":[52],"desired":[55],"vary":[57],"among":[58],"customers":[59],"environments,":[61],"it":[63],"is":[64,113,154,177],"hard":[65],"collect":[67],"for":[70,184],"all":[71],"objects.":[72],"In":[73],"addition,":[74],"occur":[77],"from":[78],"time":[79,81],"that":[82],"contained":[85],"training":[88],"data.":[89,109],"aims":[92],"learn":[94,116],"on-the-fly":[97],"after":[98],"deployment":[99],"robot,":[102],"without":[103],"pre-defined":[107],"A":[110,148],"practical":[111],"system":[112,176],"proposed":[114,156,175],"a":[117,124,181],"1.5":[121],"minutes":[122],"15":[128],"25":[130],"minutes,":[131],"integrating":[133],"state-of-the-art":[134],"works":[135],"including":[136],"online":[137],"incremental":[139,150],"salient":[141],"detection,":[142,144],"object":[143,151],"tracking,":[145],"re-identification,":[146],"etc.":[147],"novel":[149],"detection":[152],"framework":[153],"further":[155],"with":[157],"better":[158],"performance":[159,188],"than":[160],"state-of-the-arts.":[162],"Extensive":[163],"evaluations":[164],"conducted":[166],"examine":[168],"contribution":[170],"each":[172],"module.":[173],"The":[174],"also":[178],"deployed":[179],"real":[182],"robot":[183],"end":[185,187],"test.":[189]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
