{"id":"https://openalex.org/W4308057280","doi":"https://doi.org/10.1109/tnnls.2022.3214993","title":"Diversity-Learning Block: Conquer Feature Homogenization of Multibranch","display_name":"Diversity-Learning Block: Conquer Feature Homogenization of Multibranch","publication_year":2022,"publication_date":"2022-11-04","ids":{"openalex":"https://openalex.org/W4308057280","doi":"https://doi.org/10.1109/tnnls.2022.3214993","pmid":"https://pubmed.ncbi.nlm.nih.gov/36322499"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2022.3214993","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2022.3214993","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"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 Neural Networks and Learning Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5100703288","display_name":"Junjie Yang","orcid":"https://orcid.org/0000-0002-2159-1423"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Junjie Yang","raw_affiliation_strings":["SMILES Laboratory, School of Electronics and Information Engineering, Xi’an Jiaotong University, Xi’an, China"],"raw_orcid":"https://orcid.org/0000-0002-2159-1423","affiliations":[{"raw_affiliation_string":"SMILES Laboratory, School of Electronics and Information Engineering, Xi’an Jiaotong University, Xi’an, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101685414","display_name":"Shenqi Lai","orcid":"https://orcid.org/0000-0001-8673-2218"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shenqi Lai","raw_affiliation_strings":["FABU.ai, Hangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"FABU.ai, Hangzhou, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100329000","display_name":"Xuan Wang","orcid":"https://orcid.org/0000-0002-5803-2086"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuan Wang","raw_affiliation_strings":["SMILES Laboratory, School of Electronics and Information Engineering, Xi’an Jiaotong University, Xi’an, China"],"raw_orcid":"https://orcid.org/0000-0002-5803-2086","affiliations":[{"raw_affiliation_string":"SMILES Laboratory, School of Electronics and Information Engineering, Xi’an Jiaotong University, Xi’an, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101651167","display_name":"Yaxiong Wang","orcid":"https://orcid.org/0000-0001-6596-8117"},"institutions":[{"id":"https://openalex.org/I4210123185","display_name":"Zhejiang Lab","ror":"https://ror.org/02m2h7991","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210123185"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yaxiong Wang","raw_affiliation_strings":["Zhejiang Univeristy and the Zhejiang Lab, Hangzhou, China"],"raw_orcid":"https://orcid.org/0000-0001-6596-8117","affiliations":[{"raw_affiliation_string":"Zhejiang Univeristy and the Zhejiang Lab, Hangzhou, China","institution_ids":["https://openalex.org/I4210123185"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5014825654","display_name":"Xueming Qian","orcid":"https://orcid.org/0000-0002-3173-6307"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xueming Qian","raw_affiliation_strings":["Ministry of Education Key Laboratory for Intelligent Networks and Network Security, and the SMILES Laboratory, Xi’an Jiaotong University, Xi’an, China"],"raw_orcid":"https://orcid.org/0000-0002-3173-6307","affiliations":[{"raw_affiliation_string":"Ministry of Education Key Laboratory for Intelligent Networks and Network Security, and the SMILES Laboratory, Xi’an Jiaotong University, Xi’an, China","institution_ids":["https://openalex.org/I87445476"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5100703288"],"corresponding_institution_ids":["https://openalex.org/I87445476"],"apc_list":null,"apc_paid":null,"fwci":0.9184,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.75578209,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":"35","issue":"6","first_page":"7563","last_page":"7576"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":1.0,"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/T10036","display_name":"Advanced Neural Network Applications","score":1.0,"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":0.9994000196456909,"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/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9991999864578247,"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":0.7477949857711792},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6166887879371643},{"id":"https://openalex.org/keywords/flops","display_name":"FLOPS","score":0.588493824005127},{"id":"https://openalex.org/keywords/pascal","display_name":"Pascal (unit)","score":0.565131664276123},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5523484945297241},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5266225934028625},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5023913383483887},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.42078715562820435},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.4153202772140503},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.34772419929504395},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.23571312427520752},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11291015148162842}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7477949857711792},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6166887879371643},{"id":"https://openalex.org/C3826847","wikidata":"https://www.wikidata.org/wiki/Q188768","display_name":"FLOPS","level":2,"score":0.588493824005127},{"id":"https://openalex.org/C75608658","wikidata":"https://www.wikidata.org/wiki/Q44395","display_name":"Pascal (unit)","level":2,"score":0.565131664276123},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5523484945297241},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5266225934028625},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5023913383483887},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.42078715562820435},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.4153202772140503},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.34772419929504395},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.23571312427520752},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11291015148162842},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"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":2,"locations":[{"id":"doi:10.1109/tnnls.2022.3214993","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2022.3214993","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"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 Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:36322499","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/36322499","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on neural networks and learning systems","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.7599999904632568,"id":"https://metadata.un.org/sdg/11"}],"awards":[{"id":"https://openalex.org/G3308505718","display_name":null,"funder_award_id":"61732008","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7987947441","display_name":null,"funder_award_id":"61772407","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8157936946","display_name":null,"funder_award_id":"62272380","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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":63,"referenced_works":["https://openalex.org/W1836465849","https://openalex.org/W2108598243","https://openalex.org/W2145607950","https://openalex.org/W2160613239","https://openalex.org/W2183341477","https://openalex.org/W2194775991","https://openalex.org/W2302255633","https://openalex.org/W2340897893","https://openalex.org/W2412782625","https://openalex.org/W2620983607","https://openalex.org/W2752782242","https://openalex.org/W2767210436","https://openalex.org/W2787091153","https://openalex.org/W2883780447","https://openalex.org/W2922509574","https://openalex.org/W2928165649","https://openalex.org/W2959071612","https://openalex.org/W2963037463","https://openalex.org/W2963125010","https://openalex.org/W2963163009","https://openalex.org/W2963216524","https://openalex.org/W2963446712","https://openalex.org/W2963821229","https://openalex.org/W2963855133","https://openalex.org/W2963918968","https://openalex.org/W2967733054","https://openalex.org/W2981609437","https://openalex.org/W2982083293","https://openalex.org/W3034429256","https://openalex.org/W3035414587","https://openalex.org/W3082940395","https://openalex.org/W3088460296","https://openalex.org/W3098389804","https://openalex.org/W3107401984","https://openalex.org/W3113272803","https://openalex.org/W3113397624","https://openalex.org/W3118608800","https://openalex.org/W3165352316","https://openalex.org/W3167976421","https://openalex.org/W3170226651","https://openalex.org/W3171038842","https://openalex.org/W3173759468","https://openalex.org/W3179205840","https://openalex.org/W4220790454","https://openalex.org/W4297032809","https://openalex.org/W4297665946","https://openalex.org/W4297775537","https://openalex.org/W6620707391","https://openalex.org/W6637373629","https://openalex.org/W6684191040","https://openalex.org/W6737664043","https://openalex.org/W6738686954","https://openalex.org/W6747806236","https://openalex.org/W6751763797","https://openalex.org/W6754259177","https://openalex.org/W6756887525","https://openalex.org/W6765749687","https://openalex.org/W6766029800","https://openalex.org/W6775845032","https://openalex.org/W6780747106","https://openalex.org/W6786247055","https://openalex.org/W6787972765","https://openalex.org/W6947681574"],"related_works":["https://openalex.org/W4315697128","https://openalex.org/W3102845713","https://openalex.org/W2971502891","https://openalex.org/W3205506801","https://openalex.org/W4280599700","https://openalex.org/W2069133146","https://openalex.org/W3183570023","https://openalex.org/W1663079876","https://openalex.org/W2493838176","https://openalex.org/W4297686120"],"abstract_inverted_index":{"Visual":[0],"Geometry":[1],"Group":[2],"(VGG)-style":[3],"ConvNet":[4,100],"is":[5,93,102,163],"an":[6],"neural-network":[7],"process":[8],"units":[9],"(NPU)-friendly":[10],"network;":[11],"however,":[12],"the":[13,40,47,69,79,157,161],"accuracy":[14,177],"of":[15,43,50,86],"this":[16,34,59],"architecture":[17],"cannot":[18],"keep":[19],"up":[20],"with":[21,156,175],"other":[22],"well-designed":[23],"network":[24],"structures.":[25],"Although":[26],"some":[27],"reparameterization":[28],"methods":[29],"are":[30],"proposed":[31,150],"to":[32,67,77],"remedy":[33],"weakness,":[35],"their":[36],"performance":[37,155],"suffers":[38],"from":[39],"homogenization":[41],"issue":[42],"parallel":[44],"branches,":[45],"and":[46,89,95,123,132,140,168],"preset":[48],"shape":[49],"convolution":[51],"kernels":[52],"also":[53],"influences":[54],"spatial":[55],"perception.":[56],"To":[57,82],"address":[58],"problem,":[60],"we":[61],"propose":[62],"a":[63,97],"diversity-learning":[64],"(DL)":[65],"block":[66],"build":[68],"DLNet,":[70],"which":[71],"could":[72],"adaptively":[73],"learn":[74],"various":[75],"features":[76],"enrich":[78],"feature":[80],"space.":[81],"balance":[83],"floating":[84],"point":[85],"operations":[87],"(FLOPs)":[88],"accuracy,":[90],"groupwise":[91],"operation":[92],"introduced":[94],"finally,":[96],"lightweight":[98],"DL":[99],"DLGNet":[101,151],"obtained.":[103],"Extensive":[104],"evaluations":[105],"have":[106],"been":[107],"conducted":[108],"on":[109,180],"different":[110],"computer":[111],"vision":[112],"tasks,":[113],"e.g.,":[114],"image":[115],"classification":[116],"[Canadian":[117],"Institute":[118],"For":[119],"Advanced":[120],"Research":[121],"(CIFAR)":[122],"ImageNet],":[124],"object":[125,129],"detection":[126],"[PASCAL":[127],"visual":[128],"classes":[130],"(VOC)":[131],"Microsoft":[133],"Common":[134],"Objects":[135],"in":[136],"Context":[137],"(MS":[138],"COCO)],":[139],"semantic":[141],"segmentation":[142],"(Cityscapes).":[143],"The":[144],"experimental":[145],"results":[146],"show":[147],"that":[148],"our":[149],"can":[152],"achieve":[153],"comparable":[154],"state-of-the-art":[158],"networks":[159],"while":[160],"speed":[162],"183%":[164],"faster":[165,172],"than":[166,173],"GhostNet":[167],"even":[169],"over":[170],"600%":[171],"MobileNetV3":[174],"similar":[176],"when":[178],"running":[179],"NPU.":[181]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}