{"id":"https://openalex.org/W4385486178","doi":"https://doi.org/10.1109/access.2023.3301123","title":"Prototypes Sampling Mechanism for Class Incremental Learning","display_name":"Prototypes Sampling Mechanism for Class Incremental Learning","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4385486178","doi":"https://doi.org/10.1109/access.2023.3301123"},"language":"en","primary_location":{"is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3301123","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10201868.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_indexed_in_scopus":true,"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":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true},"type":"article","type_crossref":"journal-article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10201868.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5015332173","display_name":"Zhe Tao","orcid":"https://orcid.org/0009-0002-4409-5227"},"institutions":[{"id":"https://openalex.org/I4210096899","display_name":"Jiangsu University of Science and Technology","ror":"https://ror.org/00tyjp878","country_code":"CN","type":"funder","lineage":["https://openalex.org/I4210096899"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhe Tao","raw_affiliation_strings":["School of Computer Science, Jiangsu University of Science and Technology, Zhenjiang, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, Jiangsu University of Science and Technology, Zhenjiang, China","institution_ids":["https://openalex.org/I4210096899"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083070890","display_name":"Shucheng Huang","orcid":"https://orcid.org/0000-0002-5435-5961"},"institutions":[{"id":"https://openalex.org/I4210096899","display_name":"Jiangsu University of Science and Technology","ror":"https://ror.org/00tyjp878","country_code":"CN","type":"funder","lineage":["https://openalex.org/I4210096899"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shucheng Huang","raw_affiliation_strings":["School of Computer Science, Jiangsu University of Science and Technology, Zhenjiang, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, Jiangsu University of Science and Technology, Zhenjiang, China","institution_ids":["https://openalex.org/I4210096899"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5030984174","display_name":"Gang Wang","orcid":"https://orcid.org/0000-0002-8255-7165"},"institutions":[{"id":"https://openalex.org/I4210096899","display_name":"Jiangsu University of Science and Technology","ror":"https://ror.org/00tyjp878","country_code":"CN","type":"funder","lineage":["https://openalex.org/I4210096899"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Gang Wang","raw_affiliation_strings":["School of Computer Science, Jiangsu University of Science and Technology, Zhenjiang, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, Jiangsu University of Science and Technology, Zhenjiang, China","institution_ids":["https://openalex.org/I4210096899"]}]}],"institution_assertions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.812,"has_fulltext":true,"fulltext_origin":"pdf","cited_by_count":3,"citation_normalized_percentile":{"value":0.790601,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":82,"max":85},"biblio":{"volume":"11","issue":null,"first_page":"81942","last_page":"81952"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9997,"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":0.9997,"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":0.9909,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9664,"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/incremental-learning","display_name":"Incremental Learning","score":0.7050698},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.539164}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7918253},{"id":"https://openalex.org/C2780735816","wikidata":"https://www.wikidata.org/wiki/Q28324931","display_name":"Incremental learning","level":2,"score":0.7050698},{"id":"https://openalex.org/C7149132","wikidata":"https://www.wikidata.org/wiki/Q1377840","display_name":"Forgetting","level":2,"score":0.7031929},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6438862},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6417386},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.55411446},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.539164},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.5388728},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.4714219},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.42567122},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.39614892},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.33994788},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3301123","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10201868.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_indexed_in_scopus":true,"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":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true}],"best_oa_location":{"is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3301123","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10201868.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_indexed_in_scopus":true,"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":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true},"sustainable_development_goals":[{"score":0.56,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"},{"score":0.41,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, justice, and strong institutions"}],"grants":[{"funder":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China","award_id":"61772244"},{"funder":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China","award_id":"62276118"}],"datasets":[],"versions":[],"referenced_works_count":42,"referenced_works":["https://openalex.org/W1579705726","https://openalex.org/W1690739335","https://openalex.org/W1821462560","https://openalex.org/W2018124860","https://openalex.org/W2037979274","https://openalex.org/W2095705004","https://openalex.org/W2115599650","https://openalex.org/W2116522068","https://openalex.org/W2294370754","https://openalex.org/W2473930607","https://openalex.org/W2554616628","https://openalex.org/W2560647685","https://openalex.org/W2583761661","https://openalex.org/W2739879705","https://openalex.org/W2783538964","https://openalex.org/W2786446225","https://openalex.org/W2786958491","https://openalex.org/W2804175194","https://openalex.org/W2887783173","https://openalex.org/W2934243672","https://openalex.org/W2942810103","https://openalex.org/W2948734064","https://openalex.org/W2962707369","https://openalex.org/W2963072899","https://openalex.org/W2963140444","https://openalex.org/W2963314614","https://openalex.org/W2963559848","https://openalex.org/W2963588172","https://openalex.org/W2963813679","https://openalex.org/W2964067969","https://openalex.org/W2964189064","https://openalex.org/W2972313371","https://openalex.org/W3030364939","https://openalex.org/W3096831136","https://openalex.org/W3163939464","https://openalex.org/W3178686235","https://openalex.org/W3180392831","https://openalex.org/W3212150209","https://openalex.org/W4225484930","https://openalex.org/W4301163820","https://openalex.org/W4319988532","https://openalex.org/W4381249272"],"related_works":["https://openalex.org/W4382021137","https://openalex.org/W4381322349","https://openalex.org/W4297634446","https://openalex.org/W4292793971","https://openalex.org/W4287067590","https://openalex.org/W3192176272","https://openalex.org/W3186262193","https://openalex.org/W3157400488","https://openalex.org/W3034933965","https://openalex.org/W2892655153"],"abstract_inverted_index":{"Incremental":[0],"learning":[1,14,30],"aims":[2],"to":[3,63,67,89,106,110,137],"alleviate":[4],"the":[5,37,58,91,101,111,116,120,123,129,155],"catastrophic":[6],"forgetting":[7],"problem":[8,19],"of":[9,39,159],"deep":[10,81],"neural":[11],"networks":[12],"during":[13],"sequential":[15],"data":[16,26,85],"stream.":[17],"This":[18],"is":[20,27],"even":[21],"more":[22],"challenging":[23],"when":[24],"old":[25,74,96,132],"unavailable,":[28],"since":[29],"system":[31],"can":[32],"only":[33],"be":[34],"trained":[35,87],"under":[36],"supervision":[38],"current":[40,84,124],"data.":[41,125],"To":[42],"address":[43],"this":[44],"problem,":[45],"we":[46,61,104,164],"proposed":[47,62,105,161],"a":[48,108],"prototype":[49],"sampling":[50],"mechanism":[51],"based":[52,114],"on":[53,115,145,174],"K-means":[54,65],"clustering":[55,66],"method.":[56,162],"On":[57,100],"one":[59],"hand,":[60,103],"use":[64],"pick":[68],"out":[69],"class-representative":[70],"prototypes":[71,79,121],"for":[72],"each":[73],"class.":[75],"During":[76],"incremental":[77,167],"stages,":[78],"and":[80,93,97,122,133,152,157,172],"features":[82],"from":[83],"are":[86],"together":[88],"maintain":[90],"distinction":[92],"balance":[94],"between":[95,119,131],"new":[98,134],"classes.":[99],"other":[102],"attach":[107],"mask":[109],"loss":[112],"function":[113],"cosine":[117],"similarity":[118],"Which":[126],"further":[127],"enhances":[128],"discrimination":[130],"classes":[135],"compared":[136],"naive":[138],"knowledge":[139],"distillation":[140],"schemes.":[141],"Extensive":[142],"experiments":[143],"conducted":[144],"three":[146,175],"benchmark":[147],"datasets":[148,176],"including":[149],"CIFAR100,":[150],"Tiny-ImageNet":[151],"vggface2":[153],"verified":[154],"effectiveness":[156],"advantages":[158],"our":[160],"Specifically,":[163],"improved":[165],"class":[166],"performance":[168],"by":[169],"1.6%,":[170],"1.2%":[171],"1.7%":[173],"respectively.":[177]},"abstract_inverted_index_v3":null,"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W4385486178","counts_by_year":[{"year":2024,"cited_by_count":2}],"updated_date":"2025-04-22T12:53:15.757615","created_date":"2023-08-03"}