{"id":"https://openalex.org/W3090140268","doi":"https://doi.org/10.1145/3341095","title":"DenseNet-201-Based Deep Neural Network with Composite Learning Factor and Precomputation for Multiple Sclerosis Classification","display_name":"DenseNet-201-Based Deep Neural Network with Composite Learning Factor and Precomputation for Multiple Sclerosis Classification","publication_year":2020,"publication_date":"2020-04-30","ids":{"openalex":"https://openalex.org/W3090140268","doi":"https://doi.org/10.1145/3341095","mag":"3090140268"},"language":"en","primary_location":{"id":"doi:10.1145/3341095","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3341095","pdf_url":null,"source":{"id":"https://openalex.org/S19610489","display_name":"ACM Transactions on Multimedia Computing Communications and Applications","issn_l":"1551-6857","issn":["1551-6857","1551-6865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Multimedia Computing, Communications, and Applications","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":"https://openalex.org/A5007987858","display_name":"Shuihua Wang\u200e","orcid":"https://orcid.org/0000-0003-4713-2791"},"institutions":[{"id":"https://openalex.org/I143804889","display_name":"Loughborough University","ror":"https://ror.org/04vg4w365","country_code":"GB","type":"education","lineage":["https://openalex.org/I143804889"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Shui-Hua Wang","raw_affiliation_strings":["School of Architecture Building and Civil Engineering, Loughborough University, Loughborough, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Architecture Building and Civil Engineering, Loughborough University, Loughborough, UK","institution_ids":["https://openalex.org/I143804889"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100434437","display_name":"Yudong Zhang","orcid":"https://orcid.org/0000-0002-4870-1493"},"institutions":[{"id":"https://openalex.org/I153648349","display_name":"University of Leicester","ror":"https://ror.org/04h699437","country_code":"GB","type":"education","lineage":["https://openalex.org/I153648349"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Yu-Dong Zhang","raw_affiliation_strings":["Department of Informatics, University of Leicester, Leicester, Leicestershire, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Informatics, University of Leicester, Leicester, Leicestershire, UK","institution_ids":["https://openalex.org/I153648349"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":15.9627,"has_fulltext":false,"cited_by_count":271,"citation_normalized_percentile":{"value":0.99575467,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":"16","issue":"2s","first_page":"1","last_page":"19"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12874","display_name":"Digital Imaging for Blood Diseases","score":0.9821000099182129,"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/T12874","display_name":"Digital Imaging for Blood Diseases","score":0.9821000099182129,"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/T10057","display_name":"Face and Expression Recognition","score":0.9700000286102295,"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/T12702","display_name":"Brain Tumor Detection and Classification","score":0.9643999934196472,"subfield":{"id":"https://openalex.org/subfields/2808","display_name":"Neurology"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/precomputation","display_name":"Precomputation","score":0.8805370330810547},{"id":"https://openalex.org/keywords/hyperparameter","display_name":"Hyperparameter","score":0.8150522708892822},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6880174279212952},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.6842376589775085},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6033825874328613},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5803301930427551},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5290328860282898},{"id":"https://openalex.org/keywords/factor","display_name":"Factor (programming language)","score":0.506553053855896},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4973457157611847},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4949766993522644},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.372123658657074},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.1784926950931549},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.09977132081985474}],"concepts":[{"id":"https://openalex.org/C159379195","wikidata":"https://www.wikidata.org/wiki/Q7239568","display_name":"Precomputation","level":3,"score":0.8805370330810547},{"id":"https://openalex.org/C8642999","wikidata":"https://www.wikidata.org/wiki/Q4171168","display_name":"Hyperparameter","level":2,"score":0.8150522708892822},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6880174279212952},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.6842376589775085},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6033825874328613},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5803301930427551},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5290328860282898},{"id":"https://openalex.org/C2781039887","wikidata":"https://www.wikidata.org/wiki/Q1391724","display_name":"Factor (programming language)","level":2,"score":0.506553053855896},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4973457157611847},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4949766993522644},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.372123658657074},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.1784926950931549},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.09977132081985474},{"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":[{"id":"doi:10.1145/3341095","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3341095","pdf_url":null,"source":{"id":"https://openalex.org/S19610489","display_name":"ACM Transactions on Multimedia Computing Communications and Applications","issn_l":"1551-6857","issn":["1551-6857","1551-6865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Multimedia Computing, Communications, and Applications","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.6499999761581421}],"awards":[{"id":"https://openalex.org/G4792865252","display_name":null,"funder_award_id":"Y18F010018","funder_id":"https://openalex.org/F4320338464","funder_display_name":"Natural Science Foundation of Zhejiang Province"},{"id":"https://openalex.org/G8140985224","display_name":null,"funder_award_id":"61602250, 11502090, U1711263, U1811264","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"},{"id":"https://openalex.org/F4320338464","display_name":"Natural Science Foundation of Zhejiang Province","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W1148496451","https://openalex.org/W1686810756","https://openalex.org/W1981166908","https://openalex.org/W2026370547","https://openalex.org/W2027285375","https://openalex.org/W2050329937","https://openalex.org/W2090797242","https://openalex.org/W2108154570","https://openalex.org/W2109178466","https://openalex.org/W2194775991","https://openalex.org/W2312523840","https://openalex.org/W2345189929","https://openalex.org/W2498450017","https://openalex.org/W2584922303","https://openalex.org/W2618241468","https://openalex.org/W2754235618","https://openalex.org/W2758602683","https://openalex.org/W2762641225","https://openalex.org/W2783272959","https://openalex.org/W2787890383","https://openalex.org/W2791596545","https://openalex.org/W2792545481","https://openalex.org/W2792617803","https://openalex.org/W2796089230","https://openalex.org/W2801165650","https://openalex.org/W2808597956","https://openalex.org/W2822024738","https://openalex.org/W2885452141","https://openalex.org/W2900570788","https://openalex.org/W2902753032","https://openalex.org/W2905877654","https://openalex.org/W2909332287","https://openalex.org/W2910182844","https://openalex.org/W2910342037","https://openalex.org/W2912250162","https://openalex.org/W2912500072","https://openalex.org/W2923146325","https://openalex.org/W3024539712"],"related_works":["https://openalex.org/W4206951940","https://openalex.org/W4293868382","https://openalex.org/W4382602594","https://openalex.org/W3183901164","https://openalex.org/W3135818718","https://openalex.org/W4290188444","https://openalex.org/W3176438653","https://openalex.org/W3167935049","https://openalex.org/W3003905048","https://openalex.org/W2253429366"],"abstract_inverted_index":{"(":[0,47,130,192],"Aim":[1],")":[2,49,132,194],"Multiple":[3],"sclerosis":[4,37],"is":[5],"a":[6,43,65,98],"neurological":[7],"condition":[8],"that":[9,70,135],"may":[10],"cause":[11],"neurologic":[12],"disability.":[13],"Convolutional":[14],"neural":[15,54],"network":[16],"can":[17,171],"achieve":[18,172],"good":[19],"results,":[20],"but":[21],"tuning":[22],"hyperparameters":[23],"of":[24,64,78,147,154,161,169,181],"CNN":[25],"needs":[26],"expert":[27],"knowledge":[28],"and":[29,32,52,85,110,114,126,156,179,188],"are":[30,143,149,163],"difficult":[31],"time-consuming.":[33],"To":[34],"identify":[35],"multiple":[36],"more":[38],"accurately,":[39],"this":[40,204],"article":[41],"proposed":[42,61],"new":[44,159],"transfer-learning-based":[45],"approach.":[46],"Method":[48],"DenseNet-121,":[50],"DenseNet-169,":[51],"DenseNet-201":[53],"networks":[55],"were":[56,112],"compared.":[57,115],"In":[58],"addition,":[59],"we":[60],"the":[62,123,128,145,157,173],"use":[63],"composite":[66,205],"learning":[67,73,103,152,167,206,214],"factor":[68,74,153,168,215],"(CLF)":[69],"assigns":[71],"different":[72],"to":[75,90,121,141,211],"three":[76,95],"types":[77],"layers:":[79],"early":[80],"frozen":[81],"layers,":[82,84],"middle":[83],"late":[86],"replaced":[87],"layers.":[88],"How":[89],"allocate":[91],"layers":[92,96,138,146,160],"into":[93],"those":[94],"remains":[97],"problem.":[99],"Hence,":[100],"four":[101],"transfer":[102],"settings":[104],"(viz.,":[105],"Settings":[106],"A,":[107],"B,":[108],"C,":[109],"D)":[111],"tested":[113],"A":[116],"precomputation":[117],"method":[118,196],"was":[119,183],"utilized":[120],"reduce":[122],"storage":[124],"burden":[125],"accelerate":[127],"program.":[129],"Results":[131],"We":[133],"observed":[134],"DenseNet-201-D":[136,182],"(the":[137],"from":[139],"CP":[140],"T3":[142],"frozen,":[144],"D4":[148],"updated":[150],"with":[151,166],"1,":[155],"final":[158],"FCL":[162],"randomly":[164],"initialized":[165],"10)":[170],"best":[174],"performance.":[175],"The":[176],"sensitivity,":[177],"specificity,":[178],"accuracy":[180],"98.27\u00b1":[184],"0.58,":[185],"98.35\u00b1":[186],"0.69,":[187],"98.31\u00b1":[189],"0.53,":[190],"respectively.":[191],"Conclusion":[193],"Our":[195],"gives":[197,208],"better":[198],"performances":[199],"than":[200],"state-of-the-art":[201],"approaches.":[202],"Furthermore,":[203],"rate":[207],"superior":[209],"results":[210],"traditional":[212],"simple":[213],"(SLF)":[216],"strategy.":[217]},"counts_by_year":[{"year":2026,"cited_by_count":13},{"year":2025,"cited_by_count":27},{"year":2024,"cited_by_count":64},{"year":2023,"cited_by_count":62},{"year":2022,"cited_by_count":58},{"year":2021,"cited_by_count":42},{"year":2020,"cited_by_count":4},{"year":2018,"cited_by_count":1}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}
