{"id":"https://openalex.org/W7105861638","doi":"https://doi.org/10.1109/tmm.2025.3632692","title":"Feature Dispersion Adaptation With Pre-Pooling Prototype for Continual Image Classification","display_name":"Feature Dispersion Adaptation With Pre-Pooling Prototype for Continual Image Classification","publication_year":2025,"publication_date":"2025-11-17","ids":{"openalex":"https://openalex.org/W7105861638","doi":"https://doi.org/10.1109/tmm.2025.3632692"},"language":null,"primary_location":{"id":"doi:10.1109/tmm.2025.3632692","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmm.2025.3632692","pdf_url":null,"source":{"id":"https://openalex.org/S137030581","display_name":"IEEE Transactions on Multimedia","issn_l":"1520-9210","issn":["1520-9210","1941-0077"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Multimedia","raw_type":"journal-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":null,"display_name":"Wuxuan Shi","orcid":"https://orcid.org/0000-0001-8968-0417"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wuxuan Shi","raw_affiliation_strings":["National Engineering Research Center for Multimedia Software, School of Computer Science, Wuhan University, Wuhan, China"],"raw_orcid":"https://orcid.org/0000-0001-8968-0417","affiliations":[{"raw_affiliation_string":"National Engineering Research Center for Multimedia Software, School of Computer Science, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Mang Ye","orcid":"https://orcid.org/0000-0003-3989-7655"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mang Ye","raw_affiliation_strings":["National Engineering Research Center for Multimedia Software, School of Computer Science, Wuhan University, Wuhan, China"],"raw_orcid":"https://orcid.org/0000-0003-3989-7655","affiliations":[{"raw_affiliation_string":"National Engineering Research Center for Multimedia Software, School of Computer Science, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Wei Yu","orcid":"https://orcid.org/0009-0003-3564-4965"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Yu","raw_affiliation_strings":["School of Artificial Intelligence, Wuhan University, Wuhan, China"],"raw_orcid":"https://orcid.org/0009-0003-3564-4965","affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"last","author":{"id":null,"display_name":"Bo Du","orcid":"https://orcid.org/0000-0002-0059-8458"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bo Du","raw_affiliation_strings":["National Engineering Research Center for Multimedia Software, School of Computer Science, Wuhan University, Wuhan, China"],"raw_orcid":"https://orcid.org/0000-0002-0059-8458","affiliations":[{"raw_affiliation_string":"National Engineering Research Center for Multimedia Software, School of Computer Science, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I37461747"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.7087899,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"28","issue":null,"first_page":"801","last_page":"812"},"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":0.9031000137329102,"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":0.9031000137329102,"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/T12761","display_name":"Data Stream Mining Techniques","score":0.013399999588727951,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.005799999926239252,"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/classifier","display_name":"Classifier (UML)","score":0.6133999824523926},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5318999886512756},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5152000188827515},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5120000243186951},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.5008999705314636},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4846999943256378},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.45260000228881836},{"id":"https://openalex.org/keywords/confusion","display_name":"Confusion","score":0.42739999294281006}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7803999781608582},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6403999924659729},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6133999824523926},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5318999886512756},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5152000188827515},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5120000243186951},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.5008999705314636},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.49970000982284546},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4846999943256378},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.45260000228881836},{"id":"https://openalex.org/C2781140086","wikidata":"https://www.wikidata.org/wiki/Q557945","display_name":"Confusion","level":2,"score":0.42739999294281006},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3244999945163727},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.3160000145435333},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.3093000054359436},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.30869999527931213},{"id":"https://openalex.org/C94124525","wikidata":"https://www.wikidata.org/wiki/Q912550","display_name":"Categorization","level":2,"score":0.304500013589859},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.30309998989105225},{"id":"https://openalex.org/C110083411","wikidata":"https://www.wikidata.org/wiki/Q1744628","display_name":"Statistical classification","level":2,"score":0.29350000619888306},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.29179999232292175},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.2791000008583069},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.26600000262260437},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.25699999928474426},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.25690001249313354}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tmm.2025.3632692","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmm.2025.3632692","pdf_url":null,"source":{"id":"https://openalex.org/S137030581","display_name":"IEEE Transactions on Multimedia","issn_l":"1520-9210","issn":["1520-9210","1941-0077"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Multimedia","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.7263026237487793,"display_name":"Reduced inequalities"}],"awards":[{"id":"https://openalex.org/G1790277495","display_name":null,"funder_award_id":"62376200","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G1836220556","display_name":null,"funder_award_id":"62225113","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2068814885","display_name":null,"funder_award_id":"62361166629","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8800375656","display_name":null,"funder_award_id":"62176188","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":64,"referenced_works":["https://openalex.org/W153185079","https://openalex.org/W1622676895","https://openalex.org/W1638081485","https://openalex.org/W1682403713","https://openalex.org/W2060277733","https://openalex.org/W2108598243","https://openalex.org/W2194775991","https://openalex.org/W2473930607","https://openalex.org/W2560647685","https://openalex.org/W2786446225","https://openalex.org/W2884282566","https://openalex.org/W2932399282","https://openalex.org/W2948734064","https://openalex.org/W2948978827","https://openalex.org/W2954929116","https://openalex.org/W2964189064","https://openalex.org/W2972313371","https://openalex.org/W2979579363","https://openalex.org/W2981864462","https://openalex.org/W2995139074","https://openalex.org/W2998792609","https://openalex.org/W3004127093","https://openalex.org/W3034369739","https://openalex.org/W3034601242","https://openalex.org/W3035501943","https://openalex.org/W3035524453","https://openalex.org/W3047363187","https://openalex.org/W3106217498","https://openalex.org/W3107810305","https://openalex.org/W3163939464","https://openalex.org/W3168068006","https://openalex.org/W3168149265","https://openalex.org/W3175613352","https://openalex.org/W3178686235","https://openalex.org/W3202329792","https://openalex.org/W3213192039","https://openalex.org/W3216968833","https://openalex.org/W4221161784","https://openalex.org/W4280616225","https://openalex.org/W4281571140","https://openalex.org/W4295789386","https://openalex.org/W4312309344","https://openalex.org/W4312640688","https://openalex.org/W4312754066","https://openalex.org/W4312980183","https://openalex.org/W4313028293","https://openalex.org/W4313137235","https://openalex.org/W4385863749","https://openalex.org/W4386075557","https://openalex.org/W4386076561","https://openalex.org/W4387105517","https://openalex.org/W4390872637","https://openalex.org/W4390872784","https://openalex.org/W4391946799","https://openalex.org/W4393147609","https://openalex.org/W4396542737","https://openalex.org/W4396680518","https://openalex.org/W4399039651","https://openalex.org/W4399526979","https://openalex.org/W4399618322","https://openalex.org/W4400680576","https://openalex.org/W4402703021","https://openalex.org/W4402716121","https://openalex.org/W4404546514"],"related_works":[],"abstract_inverted_index":{"Catastrophic":[0],"forgetting,":[1,90],"the":[2,54,57,123,127,136,140,152,161,169,173,183],"degradation":[3],"of":[4,53,59,68,126,154,164,185],"knowledge":[5,52],"about":[6],"previously":[7],"seen":[8],"classes":[9,61,71,129],"when":[10,167],"learning":[11,26],"new":[12,55],"concepts":[13],"from":[14,107],"a":[15,20,84,113,146],"shifting":[16],"data":[17],"stream,":[18],"is":[19],"pitfall":[21],"faced":[22],"by":[23,157],"neural":[24],"network":[25],"in":[27,87,95,160],"open":[28],"environments.":[29],"Recent":[30],"research":[31],"on":[32,38,122,179],"continual":[33],"image":[34],"classification":[35],"usually":[36],"relies":[37],"storing":[39],"samples":[40],"or":[41],"prototypes":[42,125],"to":[43,66,76,103,130,138,150],"resist":[44],"this":[45,99,105],"forgetting.":[46],"We":[47],"find":[48],"that":[49],"during":[50],"acquiring":[51],"classes,":[56],"features":[58,69],"old":[60,128],"gradually":[62],"disperse,":[63],"which":[64,91,118],"leads":[65],"confusion":[67],"between":[70],"and":[72,134],"makes":[73],"them":[74],"difficult":[75],"discriminate.":[77],"Coping":[78],"with":[79,172],"feature":[80,115,132,155],"dispersion":[81,133,156],"would":[82],"be":[83],"key":[85],"consideration":[86],"resisting":[88],"catastrophic":[89],"has":[92],"been":[93],"neglected":[94],"previous":[96,174],"works.":[97],"To":[98],"end,":[100],"we":[101,111,144],"try":[102],"address":[104],"issue":[106],"two":[108],"perspectives.":[109],"First,":[110],"propose":[112],"dispersing":[114],"generation":[116],"mechanism,":[117],"generates":[119],"pseudo-features":[120],"based":[121],"pre-pooling":[124],"simulate":[131],"remind":[135],"classifier":[137],"adjust":[139],"decision":[141],"boundary.":[142],"Second,":[143],"design":[145],"consistent":[147],"alignment":[148],"constraint":[149],"alleviate":[151],"severity":[153],"maintaining":[158],"consistency":[159],"hidden":[162],"states":[163],"different":[165],"depths":[166],"aligning":[168],"current":[170],"model":[171],"model.":[175],"Extensive":[176],"experimental":[177],"results":[178],"various":[180],"benchmarks":[181],"show":[182],"superiority":[184],"our":[186],"proposed":[187],"method.":[188]},"counts_by_year":[],"updated_date":"2026-01-10T23:39:48.068659","created_date":"2025-11-17T00:00:00"}
