{"id":"https://openalex.org/W4391164109","doi":"https://doi.org/10.1109/tnnls.2023.3348657","title":"Hybrid Gromov\u2013Wasserstein Embedding for Capsule Learning","display_name":"Hybrid Gromov\u2013Wasserstein Embedding for Capsule Learning","publication_year":2024,"publication_date":"2024-01-24","ids":{"openalex":"https://openalex.org/W4391164109","doi":"https://doi.org/10.1109/tnnls.2023.3348657","pmid":"https://pubmed.ncbi.nlm.nih.gov/38265908"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2023.3348657","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2023.3348657","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":true,"oa_status":"green","oa_url":"https://digibug.ugr.es/bitstream/10481/91950/1/PRE%20PRINT%202209.00232v2.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5079232252","display_name":"Pourya Shamsolmoali","orcid":"https://orcid.org/0000-0002-0263-1661"},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Pourya Shamsolmoali","raw_affiliation_strings":["School of Communication and Electronic Engineering, East China Normal University, Shanghai, China","EEECS, Queen's University Belfast, Belfast, U.K"],"affiliations":[{"raw_affiliation_string":"School of Communication and Electronic Engineering, East China Normal University, Shanghai, China","institution_ids":["https://openalex.org/I66867065"]},{"raw_affiliation_string":"EEECS, Queen's University Belfast, Belfast, U.K","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009550171","display_name":"Masoumeh Zareapoor","orcid":"https://orcid.org/0000-0002-3991-0584"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Masoumeh Zareapoor","raw_affiliation_strings":["Department of Electrical Engineering, Shanghai Jiao Tong University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000078546","display_name":"Swagatam Das","orcid":"https://orcid.org/0000-0001-6843-4508"},"institutions":[{"id":"https://openalex.org/I6498739","display_name":"Indian Statistical Institute","ror":"https://ror.org/00q2w1j53","country_code":"IN","type":"education","lineage":["https://openalex.org/I6498739"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Swagatam Das","raw_affiliation_strings":["Electronics and Communication Sciences Unit, Indian Statistical Institute, Kolkata, India","Institute for Advancing Intelligence, TCG CREST, Kolkata, India"],"affiliations":[{"raw_affiliation_string":"Electronics and Communication Sciences Unit, Indian Statistical Institute, Kolkata, India","institution_ids":["https://openalex.org/I6498739"]},{"raw_affiliation_string":"Institute for Advancing Intelligence, TCG CREST, Kolkata, India","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006937759","display_name":"\u00c9ric Granger","orcid":"https://orcid.org/0000-0001-6116-7945"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Eric Granger","raw_affiliation_strings":["Department of Systems Engineering, École de technologie supérieure, Université du Québec, Montreal, QC, Canada"],"affiliations":[{"raw_affiliation_string":"Department of Systems Engineering, École de technologie supérieure, Université du Québec, Montreal, QC, Canada","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5078909305","display_name":"Salvador Garc\u00eda","orcid":"https://orcid.org/0000-0003-4494-7565"},"institutions":[{"id":"https://openalex.org/I173304897","display_name":"Universidad de Granada","ror":"https://ror.org/04njjy449","country_code":"ES","type":"education","lineage":["https://openalex.org/I173304897"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Salvador Garc\u00eda","raw_affiliation_strings":["Department of Computer Science and Artificial Intelligence, University of Granada, Granada, Spain"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Artificial Intelligence, University of Granada, Granada, Spain","institution_ids":["https://openalex.org/I173304897"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5079232252"],"corresponding_institution_ids":["https://openalex.org/I66867065"],"apc_list":null,"apc_paid":null,"fwci":1.0146,"has_fulltext":true,"cited_by_count":4,"citation_normalized_percentile":{"value":0.74889426,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":98},"biblio":{"volume":"36","issue":"2","first_page":"2480","last_page":"2494"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9994999766349792,"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":0.9994999766349792,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9976999759674072,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9936000108718872,"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":0.7228488922119141},{"id":"https://openalex.org/keywords/interpretability","display_name":"Interpretability","score":0.6795127391815186},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.619296133518219},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6026244163513184},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4518413841724396},{"id":"https://openalex.org/keywords/component","display_name":"Component (thermodynamics)","score":0.4139939248561859},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.39706936478614807}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7228488922119141},{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.6795127391815186},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.619296133518219},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6026244163513184},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4518413841724396},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.4139939248561859},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.39706936478614807},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/tnnls.2023.3348657","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2023.3348657","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:38265908","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/38265908","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},{"id":"pmh:oai:digibug.ugr.es:10481/91950","is_oa":true,"landing_page_url":"https://hdl.handle.net/10481/91950","pdf_url":"https://digibug.ugr.es/bitstream/10481/91950/1/PRE%20PRINT%202209.00232v2.pdf","source":{"id":"https://openalex.org/S4306400567","display_name":"Institutional Repository of the University of Granada (University of Granada)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I173304897","host_organization_name":"Universidad de Granada","host_organization_lineage":["https://openalex.org/I173304897"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-sa","license_id":"https://openalex.org/licenses/cc-by-nc-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"info:eu-repo/semantics/article"},{"id":"pmh:oai:espace2.etsmtl.ca:28403","is_oa":false,"landing_page_url":"https://espace2.etsmtl.ca/id/eprint/28403/","pdf_url":null,"source":{"id":"https://openalex.org/S4306402392","display_name":"Espace \u00c9TS (ETS)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1341030882","host_organization_name":"Educational Testing Service","host_organization_lineage":["https://openalex.org/I1341030882"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Article publi\u00e9 dans une revue, r\u00e9vis\u00e9 par les pairs"}],"best_oa_location":{"id":"pmh:oai:digibug.ugr.es:10481/91950","is_oa":true,"landing_page_url":"https://hdl.handle.net/10481/91950","pdf_url":"https://digibug.ugr.es/bitstream/10481/91950/1/PRE%20PRINT%202209.00232v2.pdf","source":{"id":"https://openalex.org/S4306400567","display_name":"Institutional Repository of the University of Granada (University of Granada)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I173304897","host_organization_name":"Universidad de Granada","host_organization_lineage":["https://openalex.org/I173304897"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-sa","license_id":"https://openalex.org/licenses/cc-by-nc-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"info:eu-repo/semantics/article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4391164109.pdf","grobid_xml":"https://content.openalex.org/works/W4391164109.grobid-xml"},"referenced_works_count":86,"referenced_works":["https://openalex.org/W1889081078","https://openalex.org/W1901129140","https://openalex.org/W1968625547","https://openalex.org/W1970958500","https://openalex.org/W2027842533","https://openalex.org/W2036996178","https://openalex.org/W2037227137","https://openalex.org/W2108598243","https://openalex.org/W2112796928","https://openalex.org/W2134557905","https://openalex.org/W2194775991","https://openalex.org/W2335728318","https://openalex.org/W2417433140","https://openalex.org/W2559597482","https://openalex.org/W2613783066","https://openalex.org/W2630837129","https://openalex.org/W2740418457","https://openalex.org/W2752782242","https://openalex.org/W2932083555","https://openalex.org/W2945830552","https://openalex.org/W2963472233","https://openalex.org/W2964137095","https://openalex.org/W2981413347","https://openalex.org/W2982147654","https://openalex.org/W2997891818","https://openalex.org/W3003482062","https://openalex.org/W3017063488","https://openalex.org/W3118608800","https://openalex.org/W3132401450","https://openalex.org/W3157122767","https://openalex.org/W3168997536","https://openalex.org/W3176241179","https://openalex.org/W3186928351","https://openalex.org/W3214585531","https://openalex.org/W4213437519","https://openalex.org/W4214841728","https://openalex.org/W4224321068","https://openalex.org/W4225982766","https://openalex.org/W4226154274","https://openalex.org/W4229081350","https://openalex.org/W4233762729","https://openalex.org/W4280557312","https://openalex.org/W4282942883","https://openalex.org/W4283327373","https://openalex.org/W4287231574","https://openalex.org/W4287753648","https://openalex.org/W4298333447","https://openalex.org/W4300980463","https://openalex.org/W4312376888","https://openalex.org/W4313052800","https://openalex.org/W4313291238","https://openalex.org/W4362692581","https://openalex.org/W4365443444","https://openalex.org/W4381327818","https://openalex.org/W4382203373","https://openalex.org/W4385453669","https://openalex.org/W4386076013","https://openalex.org/W6600115225","https://openalex.org/W6631190155","https://openalex.org/W6639432524","https://openalex.org/W6682962330","https://openalex.org/W6735463952","https://openalex.org/W6739696289","https://openalex.org/W6743446608","https://openalex.org/W6747043499","https://openalex.org/W6748053814","https://openalex.org/W6750207810","https://openalex.org/W6754567369","https://openalex.org/W6757500957","https://openalex.org/W6762483757","https://openalex.org/W6763665168","https://openalex.org/W6766097413","https://openalex.org/W6767084090","https://openalex.org/W6767490896","https://openalex.org/W6767766851","https://openalex.org/W6772452466","https://openalex.org/W6779830598","https://openalex.org/W6780053115","https://openalex.org/W6786579831","https://openalex.org/W6789466042","https://openalex.org/W6790082833","https://openalex.org/W6790689736","https://openalex.org/W6800433216","https://openalex.org/W6802188248","https://openalex.org/W6810837692","https://openalex.org/W6845345481"],"related_works":["https://openalex.org/W2905433371","https://openalex.org/W2888392564","https://openalex.org/W4310278675","https://openalex.org/W4388422664","https://openalex.org/W4390569940","https://openalex.org/W4361193272","https://openalex.org/W2963326959","https://openalex.org/W2809283485","https://openalex.org/W4293768783","https://openalex.org/W4288347394"],"abstract_inverted_index":{"Capsule":[0],"networks":[1],"(CapsNets)":[2],"aim":[3],"to":[4,192,221,255],"parse":[5],"images":[6],"into":[7,170],"a":[8,17,119],"hierarchy":[9],"of":[10,41,50,64,69,121,182,219],"objects,":[11],"parts,":[12],"and":[13,23,98,146,176,202,229,258,261],"their":[14,57,156,183,200],"relationships":[15],"using":[16],"two-step":[18],"process":[19],"involving":[20],"part-whole":[21],"transformation":[22],"hierarchical":[24,29,203],"component":[25,185],"routing.":[26],"However,":[27],"this":[28,83],"relationship":[30],"modeling":[31],"is":[32,128],"computationally":[33],"expensive,":[34],"which":[35,124,138],"has":[36],"limited":[37],"the":[38,66,133,141,144,147,151,174,180,217],"wider":[39],"use":[40],"CapsNet":[42,51,262],"despite":[43],"its":[44,213],"potential":[45],"advantages.":[46],"The":[47],"current":[48],"state":[49],"models":[52,97,263],"primarily":[53],"focuses":[54],"on":[55,167,179],"comparing":[56],"performance":[58,102],"with":[59,104],"capsule":[60],"baselines,":[61],"falling":[62],"short":[63],"achieving":[65],"same":[67],"level":[68],"proficiency":[70],"as":[71],"deep":[72],"convolutional":[73],"neural":[74],"network":[75],"(CNN)":[76],"variants":[77],"in":[78,113,235],"intricate":[79,223],"tasks.":[80,238,267],"To":[81],"address":[82],"limitation,":[84],"we":[85,117,131],"present":[86,132],"an":[87,125],"efficient":[88],"approach":[89,188],"for":[90],"learning":[91],"capsules":[92,220,245],"that":[93,243],"surpasses":[94],"canonical":[95],"baseline":[96,233],"even":[99],"demonstrates":[100],"superior":[101],"compared":[103],"high-performing":[105],"convolution":[106],"models.":[107],"Our":[108,205,239],"contribution":[109],"can":[110],"be":[111],"outlined":[112],"two":[114,209],"aspects:":[115],"first,":[116],"introduce":[118],"group":[120],"subcapsules":[122],"onto":[123],"input":[126,145,175],"vector":[127],"projected.":[129],"Subsequently,":[130],"hybrid":[134],"Gromov-Wasserstein":[135],"(HGW)":[136],"framework,":[137],"initially":[139],"quantifies":[140],"dissimilarity":[142],"between":[143,173],"components":[148],"modeled":[149],"by":[150,154],"subcapsules,":[152,177],"followed":[153],"determining":[155],"alignment":[157,172],"degree":[158],"through":[159],"optimal":[160],"transport":[161],"(OT).":[162],"This":[163,187],"innovative":[164],"mechanism":[165],"capitalizes":[166],"new":[168],"insights":[169],"defining":[171],"based":[178],"similarity":[181],"respective":[184],"distributions.":[186],"enhances":[189],"CapsNets'":[190],"capacity":[191],"learn":[193],"from":[194],"intricate,":[195],"high-dimensional":[196],"data":[197],"while":[198],"retaining":[199],"interpretability":[201],"structure.":[204],"proposed":[206],"model":[207],"offers":[208],"distinct":[210],"advantages:":[211],"1)":[212],"lightweight":[214],"nature":[215],"facilitates":[216],"application":[218],"more":[222],"vision":[224,266],"tasks,":[225],"including":[226],"object":[227],"detection;":[228],"2)":[230],"it":[231],"outperforms":[232],"approaches":[234],"these":[236],"demanding":[237],"empirical":[240],"findings":[241],"illustrate":[242],"HGW":[244],"(HGWCapsules)":[246],"exhibit":[247],"enhanced":[248],"robustness":[249],"against":[250],"affine":[251],"transformations,":[252],"scale":[253],"effectively":[254],"larger":[256],"datasets,":[257],"surpass":[259],"CNN":[260],"across":[264],"various":[265]},"counts_by_year":[{"year":2024,"cited_by_count":4}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}