{"id":"https://openalex.org/W3089452734","doi":"https://doi.org/10.1109/ijcnn48605.2020.9206651","title":"Analysis and Learning of Capsule Networks Robust for Small Image Deformation","display_name":"Analysis and Learning of Capsule Networks Robust for Small Image Deformation","publication_year":2020,"publication_date":"2020-07-01","ids":{"openalex":"https://openalex.org/W3089452734","doi":"https://doi.org/10.1109/ijcnn48605.2020.9206651","mag":"3089452734"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn48605.2020.9206651","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn48605.2020.9206651","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-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/A5046141164","display_name":"Nozomu Ohta","orcid":"https://orcid.org/0000-0003-3763-144X"},"institutions":[{"id":"https://openalex.org/I146399215","display_name":"University of Tsukuba","ror":"https://ror.org/02956yf07","country_code":"JP","type":"education","lineage":["https://openalex.org/I146399215"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Nozomu Ohta","raw_affiliation_strings":["Department of Intelligent Interaction Technologies, University of Tsukuba, Tsukuba-City, Japan"],"affiliations":[{"raw_affiliation_string":"Department of Intelligent Interaction Technologies, University of Tsukuba, Tsukuba-City, Japan","institution_ids":["https://openalex.org/I146399215"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042152107","display_name":"Shin Kawai","orcid":"https://orcid.org/0000-0003-3287-6093"},"institutions":[{"id":"https://openalex.org/I146399215","display_name":"University of Tsukuba","ror":"https://ror.org/02956yf07","country_code":"JP","type":"education","lineage":["https://openalex.org/I146399215"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Shin Kawai","raw_affiliation_strings":["Department of Intelligent Interaction Technologies, University of Tsukuba, Tsukuba-City, Japan"],"affiliations":[{"raw_affiliation_string":"Department of Intelligent Interaction Technologies, University of Tsukuba, Tsukuba-City, Japan","institution_ids":["https://openalex.org/I146399215"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5085264826","display_name":"Hajime Nobuhara","orcid":"https://orcid.org/0000-0002-1818-6929"},"institutions":[{"id":"https://openalex.org/I146399215","display_name":"University of Tsukuba","ror":"https://ror.org/02956yf07","country_code":"JP","type":"education","lineage":["https://openalex.org/I146399215"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Hajime Nobuhara","raw_affiliation_strings":["Department of Intelligent Interaction Technologies, University of Tsukuba, Tsukuba-City, Japan"],"affiliations":[{"raw_affiliation_string":"Department of Intelligent Interaction Technologies, University of Tsukuba, Tsukuba-City, Japan","institution_ids":["https://openalex.org/I146399215"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5046141164"],"corresponding_institution_ids":["https://openalex.org/I146399215"],"apc_list":null,"apc_paid":null,"fwci":0.2931,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.56879747,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10824","display_name":"Image Retrieval and Classification 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"}},"topics":[{"id":"https://openalex.org/T10824","display_name":"Image Retrieval and Classification 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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","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"}},{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":0.9991000294685364,"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":0.5781412124633789},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5428398251533508},{"id":"https://openalex.org/keywords/deformation","display_name":"Deformation (meteorology)","score":0.5123571157455444},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4885781705379486},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4495486319065094},{"id":"https://openalex.org/keywords/capsule","display_name":"Capsule","score":0.44127607345581055},{"id":"https://openalex.org/keywords/materials-science","display_name":"Materials science","score":0.1729663908481598},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.15578040480613708},{"id":"https://openalex.org/keywords/composite-material","display_name":"Composite material","score":0.08859005570411682}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5781412124633789},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5428398251533508},{"id":"https://openalex.org/C204366326","wikidata":"https://www.wikidata.org/wiki/Q3027650","display_name":"Deformation (meteorology)","level":2,"score":0.5123571157455444},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4885781705379486},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4495486319065094},{"id":"https://openalex.org/C2778778583","wikidata":"https://www.wikidata.org/wiki/Q147768","display_name":"Capsule","level":2,"score":0.44127607345581055},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.1729663908481598},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.15578040480613708},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.08859005570411682},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn48605.2020.9206651","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn48605.2020.9206651","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","score":0.47999998927116394,"id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W2966661","https://openalex.org/W2078455576","https://openalex.org/W2294798173","https://openalex.org/W2896342044","https://openalex.org/W2963384288","https://openalex.org/W2963703618","https://openalex.org/W2963720850","https://openalex.org/W2964318666","https://openalex.org/W2969985801","https://openalex.org/W4295238618","https://openalex.org/W4309088715","https://openalex.org/W6600115225","https://openalex.org/W6743446608","https://openalex.org/W6751741970","https://openalex.org/W6755269281"],"related_works":["https://openalex.org/W2005185696","https://openalex.org/W2161229648","https://openalex.org/W2235753890","https://openalex.org/W2993674027","https://openalex.org/W2130228941","https://openalex.org/W2092957489","https://openalex.org/W2366116130","https://openalex.org/W2314419244","https://openalex.org/W2132132164","https://openalex.org/W2889893736"],"abstract_inverted_index":{"The":[0,144],"Capsule":[1],"Network":[2],"(CapsNet)":[3],"is":[4,14,26,55,149,161],"a":[5,27,61,69,95],"deep":[6],"learning":[7,54,88,135,159],"model":[8],"proposed":[9,114,142],"for":[10,63],"image":[11],"classification":[12,51],"that":[13,147],"robust":[15],"to":[16,72,108],"pose":[17],"of":[18,20,35,43,50,100,112,137],"change":[19],"objects":[21],"in":[22,90,167],"images.":[23],"A":[24],"capsule":[25,71],"vector":[28],"representing":[29],"the":[30,41,48,79,85,91,98,110,113,117,126,132,138,154,158],"position,":[31],"size":[32],"and":[33,53,119,134,141,157],"presence":[34],"an":[36,125],"object.":[37],"However,":[38],"with":[39],"CapsNet,":[40],"number":[42,49],"capsules":[44,101],"increases,":[45],"depending":[46],"on":[47,153],"classes,":[52,82],"computationally":[56],"expensive.":[57],"Thus,":[58],"we":[59,83,130],"propose":[60],"method":[62,89],"reducing":[64],"computational":[65],"costs":[66],"by":[67,104,151,163],"enabling":[68],"single":[70],"represent":[73],"multiple":[74],"object":[75],"classes.":[76],"To":[77],"learn":[78],"distance":[80,87],"between":[81],"incorporate":[84],"ArcFace":[86],"error":[92],"function.":[93],"In":[94],"preliminary":[96],"experiment,":[97],"distribution":[99],"was":[102],"visualised":[103],"principal":[105],"component":[106],"analysis":[107],"demonstrate":[109,146],"validity":[111],"method.":[115,143],"Using":[116],"MNIST":[118],"CIFAR-10":[120,155],"datasets,":[121],"as":[122,124],"well":[123],"affine":[127],"transformed":[128],"dataset,":[129,156],"compare":[131],"accuracy":[133,148],"time":[136,160],"original":[139],"CapsNet":[140],"results":[145],"improved":[150],"2.74%":[152],"reduced":[162],"more":[164],"than":[165],"19%":[166],"both":[168],"datasets.":[169]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}