乐胖代购免代理版

{"id":"https://openalex.org/W3200398484","doi":"https://doi.org/10.1109/ijcnn52387.2021.9533384","title":"Partial Transfer Learning for Fast Evolutionary Generative Adversarial Networks","display_name":"Partial Transfer Learning for Fast Evolutionary Generative Adversarial Networks","publication_year":2021,"publication_date":"2021-07-18","ids":{"openalex":"https://openalex.org/W3200398484","doi":"https://doi.org/10.1109/ijcnn52387.2021.9533384","mag":"3200398484"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn52387.2021.9533384","pdf_url":null,"source":{"id":"https://openalex.org/S4363607707","display_name":"2022 International Joint Conference on Neural Networks (IJCNN)","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":null,"is_accepted":false,"is_published":false},"type":"article","type_crossref":"proceedings-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/A5015554929","display_name":"Zheping Liu","orcid":"https://orcid.org/0000-0003-1807-6671"},"institutions":[{"id":"https://openalex.org/I82951845","display_name":"RMIT University","ror":"https://ror.org/04ttjf776","country_code":"AU","type":"education","lineage":["https://openalex.org/I82951845"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Zheping Liu","raw_affiliation_strings":["RMIT University, Melbourne, Australia"],"affiliations":[{"raw_affiliation_string":"RMIT University, Melbourne, Australia","institution_ids":["https://openalex.org/I82951845"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050621611","display_name":"Nasser R. Sabar","orcid":"https://orcid.org/0000-0002-0276-4704"},"institutions":[{"id":"https://openalex.org/I196829312","display_name":"La Trobe University","ror":"https://ror.org/01rxfrp27","country_code":"AU","type":"education","lineage":["https://openalex.org/I196829312"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Nasser Sabar","raw_affiliation_strings":["La Trobe University, Melbourne, Australia"],"affiliations":[{"raw_affiliation_string":"La Trobe University, Melbourne, Australia","institution_ids":["https://openalex.org/I196829312"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5056403144","display_name":"Andy Song","orcid":"https://orcid.org/0000-0002-7579-7048"},"institutions":[{"id":"https://openalex.org/I82951845","display_name":"RMIT University","ror":"https://ror.org/04ttjf776","country_code":"AU","type":"education","lineage":["https://openalex.org/I82951845"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Andy Song","raw_affiliation_strings":["RMIT University, Melbourne, Australia"],"affiliations":[{"raw_affiliation_string":"RMIT University, Melbourne, Australia","institution_ids":["https://openalex.org/I82951845"]}]}],"institution_assertions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.185,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.522735,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":72,"max":76},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9988,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9988,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.9815,"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.9763,"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/discriminator","display_name":"Discriminator","score":0.6739134},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.46270823}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7236853},{"id":"https://openalex.org/C2779803651","wikidata":"https://www.wikidata.org/wiki/Q5282088","display_name":"Discriminator","level":3,"score":0.6739134},{"id":"https://openalex.org/C159149176","wikidata":"https://www.wikidata.org/wiki/Q14489129","display_name":"Evolutionary algorithm","level":2,"score":0.5226295},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5058934},{"id":"https://openalex.org/C2780992000","wikidata":"https://www.wikidata.org/wiki/Q17016113","display_name":"Generator (circuit theory)","level":3,"score":0.47956723},{"id":"https://openalex.org/C105902424","wikidata":"https://www.wikidata.org/wiki/Q1197129","display_name":"Evolutionary computation","level":2,"score":0.46993026},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.46270823},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.45702383},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.45134872},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"score":0.449513},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4235712},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.34161767},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.24192885},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","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/C149923435","wikidata":"https://www.wikidata.org/wiki/Q37732","display_name":"Demography","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn52387.2021.9533384","pdf_url":null,"source":{"id":"https://openalex.org/S4363607707","display_name":"2022 International Joint Conference on Neural Networks (IJCNN)","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":null,"is_accepted":false,"is_published":false}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.71,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"grants":[],"datasets":[],"versions":[],"referenced_works_count":33,"referenced_works":["https://openalex.org/W1710476689","https://openalex.org/W1834627138","https://openalex.org/W2161381512","https://openalex.org/W2173520492","https://openalex.org/W2593414223","https://openalex.org/W2632772789","https://openalex.org/W2883069695","https://openalex.org/W2902255935","https://openalex.org/W2947956927","https://openalex.org/W2955841847","https://openalex.org/W2962760235","https://openalex.org/W2962879692","https://openalex.org/W2963373786","https://openalex.org/W2963684088","https://openalex.org/W2963981733","https://openalex.org/W2964121818","https://openalex.org/W2964201867","https://openalex.org/W2967552310","https://openalex.org/W2984648456","https://openalex.org/W2996126761","https://openalex.org/W3006168429","https://openalex.org/W3012093928","https://openalex.org/W3015889445","https://openalex.org/W3080107131","https://openalex.org/W3085696062","https://openalex.org/W3106257197","https://openalex.org/W3118608800","https://openalex.org/W3141876413","https://openalex.org/W4294643831","https://openalex.org/W4295521014","https://openalex.org/W4298289240","https://openalex.org/W4301206121","https://openalex.org/W967544008"],"related_works":["https://openalex.org/W91044377","https://openalex.org/W4297582752","https://openalex.org/W4285805405","https://openalex.org/W3133779647","https://openalex.org/W2802808995","https://openalex.org/W2787833928","https://openalex.org/W2593449396","https://openalex.org/W2391924736","https://openalex.org/W2021957875","https://openalex.org/W1560122427"],"abstract_inverted_index":{"Generative":[0],"Adversarial":[1],"Networks":[2],"(GAN)":[3],"are":[4],"well":[5],"known":[6],"for":[7],"their":[8],"capability":[9],"of":[10,21,40,59,87,110],"generating":[11],"photo-realistic":[12],"images":[13],"or":[14],"data":[15,100,118],"collections":[16],"that":[17,121],"appear":[18],"real.":[19],"One":[20],"state-of-the-art":[22],"approaches":[23],"in":[24,57,148],"GAN":[25,28,34],"is":[26,54,72,146],"Evolutionary":[27],"(E-GAN)":[29],"which":[30],"can":[31,123],"outperform":[32],"other":[33],"methods":[35],"by":[36],"leveraging":[37],"the":[38,85,93,96,104,116],"advantages":[39],"evolutionary":[41,52],"computing,":[42],"including":[43],"population":[44],"based":[45,80],"search,":[46],"mutation":[47],"and":[48,64,95,102],"elitism":[49],"operators.":[50],"However":[51],"search":[53],"often":[55],"demanding":[56],"terms":[58],"resources,":[60],"e.g.":[61],"computational":[62],"power":[63],"time.":[65],"That":[66],"limits":[67],"its":[68],"applicability":[69],"when":[70,129],"resource":[71],"limited.":[73],"Hence":[74],"we":[75],"propose":[76],"Partial":[77],"Transfer":[78],"training":[79],"E-GAN":[81,128],"(PT-EGAN)":[82],"to":[83,91,138],"improve":[84],"efficiency":[86],"E-GAN.":[88,144],"PT-EGAN":[89,122,134,145],"aims":[90],"train":[92],"generator":[94],"discriminator":[97],"with":[98],"smaller":[99],"sets":[101],"transfer":[103],"gained":[105],"features":[106],"across":[107],"different":[108],"stages":[109],"training.":[111],"Our":[112],"comparative":[113],"experiments":[114],"on":[115],"CIFAR-10":[117],"set":[119],"shows":[120],"reach":[124],"better":[125],"performance":[126,142],"than":[127],"using":[130],"similar":[131,141],"resources.":[132],"Alternatively":[133],"requires":[135],"less":[136],"resources":[137],"achieve":[139],"a":[140],"as":[143],"effective":[147],"speeding":[149],"up":[150],"generative":[151],"adversarial":[152],"learning.":[153]},"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W3200398484","counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2}],"updated_date":"2025-01-04T16:11:13.459882","created_date":"2021-09-27"}