{"id":"https://openalex.org/W2967177870","doi":"https://doi.org/10.1109/uemcon47517.2019.8993019","title":"Residual Capsule Network","display_name":"Residual Capsule Network","publication_year":2019,"publication_date":"2019-10-01","ids":{"openalex":"https://openalex.org/W2967177870","doi":"https://doi.org/10.1109/uemcon47517.2019.8993019","mag":"2967177870"},"language":"en","primary_location":{"id":"doi:10.1109/uemcon47517.2019.8993019","is_oa":false,"landing_page_url":"https://doi.org/10.1109/uemcon47517.2019.8993019","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE 10th Annual Ubiquitous Computing, Electronics &amp; Mobile Communication Conference (UEMCON)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://scholarworks.indianapolis.iu.edu/bitstreams/469d1611-eba8-4380-8dc6-1bd64dfa5251/download","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5035380088","display_name":"Sree Bala Shruthi Bhamidi","orcid":null},"institutions":[{"id":"https://openalex.org/I55769427","display_name":"Indiana University \u2013 Purdue University Indianapolis","ror":"https://ror.org/05gxnyn08","country_code":"US","type":"education","lineage":["https://openalex.org/I55769427","https://openalex.org/I592451"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sree Bala Shruthi Bhamidi","raw_affiliation_strings":["Electrical and Computer Engineering, Purdue School of Engineering, IUPUI, Indianapolis, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Electrical and Computer Engineering, Purdue School of Engineering, IUPUI, Indianapolis, USA","institution_ids":["https://openalex.org/I55769427"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5051497566","display_name":"Mohamed El\u2010Sharkawy","orcid":"https://orcid.org/0000-0002-0608-399X"},"institutions":[{"id":"https://openalex.org/I55769427","display_name":"Indiana University \u2013 Purdue University Indianapolis","ror":"https://ror.org/05gxnyn08","country_code":"US","type":"education","lineage":["https://openalex.org/I55769427","https://openalex.org/I592451"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mohamed El-Sharkawy","raw_affiliation_strings":["Electrical and Computer Engineering, Purdue School of Engineering, IUPUI, Indianapolis, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Electrical and Computer Engineering, Purdue School of Engineering, IUPUI, Indianapolis, USA","institution_ids":["https://openalex.org/I55769427"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I55769427"],"apc_list":null,"apc_paid":null,"fwci":0.8927,"has_fulltext":true,"cited_by_count":15,"citation_normalized_percentile":{"value":0.78809865,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"0557","last_page":"0560"},"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9991000294685364,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/mnist-database","display_name":"MNIST database","score":0.8396691083908081},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.8270295262336731},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6730827689170837},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6237162351608276},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6204740405082703},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.55010586977005},{"id":"https://openalex.org/keywords/transformation","display_name":"Transformation (genetics)","score":0.5222664475440979},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.46697306632995605},{"id":"https://openalex.org/keywords/pooling","display_name":"Pooling","score":0.457439661026001},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4306979477405548},{"id":"https://openalex.org/keywords/capsule","display_name":"Capsule","score":0.41330739855766296},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3942854702472687},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3844414949417114},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3756615221500397},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.28546786308288574}],"concepts":[{"id":"https://openalex.org/C190502265","wikidata":"https://www.wikidata.org/wiki/Q17069496","display_name":"MNIST database","level":3,"score":0.8396691083908081},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.8270295262336731},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6730827689170837},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6237162351608276},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6204740405082703},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.55010586977005},{"id":"https://openalex.org/C204241405","wikidata":"https://www.wikidata.org/wiki/Q461499","display_name":"Transformation (genetics)","level":3,"score":0.5222664475440979},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.46697306632995605},{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.457439661026001},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4306979477405548},{"id":"https://openalex.org/C2778778583","wikidata":"https://www.wikidata.org/wiki/Q147768","display_name":"Capsule","level":2,"score":0.41330739855766296},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3942854702472687},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3844414949417114},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3756615221500397},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.28546786308288574},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","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/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"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/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C111368507","wikidata":"https://www.wikidata.org/wiki/Q43518","display_name":"Oceanography","level":1,"score":0.0},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/uemcon47517.2019.8993019","is_oa":false,"landing_page_url":"https://doi.org/10.1109/uemcon47517.2019.8993019","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE 10th Annual Ubiquitous Computing, Electronics &amp; Mobile Communication Conference (UEMCON)","raw_type":"proceedings-article"},{"id":"pmh:oai:scholarworks.iupui.edu:1805/25166","is_oa":true,"landing_page_url":"http://hdl.handle.net/1805/25166","pdf_url":"https://scholarworks.indianapolis.iu.edu/bitstreams/469d1611-eba8-4380-8dc6-1bd64dfa5251/download","source":{"id":"https://openalex.org/S4306400987","display_name":"IUScholarWorks (Indiana University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I592451","host_organization_name":"Indiana University","host_organization_lineage":["https://openalex.org/I592451"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Author","raw_type":"Conference proceedings"},{"id":"pmh:oai:scholarworks.indianapolis.iu.edu:1805/25166","is_oa":false,"landing_page_url":"https://hdl.handle.net/1805/25166","pdf_url":null,"source":{"id":"https://openalex.org/S4306400987","display_name":"IUScholarWorks (Indiana University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I592451","host_organization_name":"Indiana University","host_organization_lineage":["https://openalex.org/I592451"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Author","raw_type":"Conference proceedings"}],"best_oa_location":{"id":"pmh:oai:scholarworks.iupui.edu:1805/25166","is_oa":true,"landing_page_url":"http://hdl.handle.net/1805/25166","pdf_url":"https://scholarworks.indianapolis.iu.edu/bitstreams/469d1611-eba8-4380-8dc6-1bd64dfa5251/download","source":{"id":"https://openalex.org/S4306400987","display_name":"IUScholarWorks (Indiana University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I592451","host_organization_name":"Indiana University","host_organization_lineage":["https://openalex.org/I592451"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Author","raw_type":"Conference proceedings"},"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","score":0.5600000023841858,"id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2967177870.pdf","grobid_xml":"https://content.openalex.org/works/W2967177870.grobid-xml"},"referenced_works_count":11,"referenced_works":["https://openalex.org/W2966661","https://openalex.org/W2112796928","https://openalex.org/W2163605009","https://openalex.org/W2194775991","https://openalex.org/W2618530766","https://openalex.org/W2775143585","https://openalex.org/W2785994986","https://openalex.org/W2963703618","https://openalex.org/W6743446608","https://openalex.org/W6747050675","https://openalex.org/W6780493881"],"related_works":["https://openalex.org/W4386603768","https://openalex.org/W2950475743","https://openalex.org/W2886711096","https://openalex.org/W2750384547","https://openalex.org/W4380078352","https://openalex.org/W3046591097","https://openalex.org/W4389249638","https://openalex.org/W2733410219","https://openalex.org/W2734358244","https://openalex.org/W4388700941"],"abstract_inverted_index":{"Convolution":[0],"Neural":[1],"Network":[2,147,150,180,198],"(CNN)":[3],"has":[4,114],"been":[5],"the":[6,11,23,53,66,78,83,86,99,111,127,143,161,171,174,187,192,195,220,227],"most":[7],"influential":[8],"innovations":[9],"in":[10,22,178,219],"filed":[12],"of":[13,25,36,68,82,145,164,194,222],"Computer":[14],"Vision.":[15],"CNN":[16,39],"have":[17,64,71,130,214],"shown":[18,72,131],"a":[19,41,73,157,216],"substantial":[20],"improvement":[21,75],"field":[24],"Machine":[26],"Learning.":[27],"But":[28],"they":[29,50,134],"do":[30],"come":[31],"with":[32,139],"their":[33],"own":[34],"set":[35],"drawbacks":[37],"-":[38],"need":[40],"large":[42],"dataset,":[43],"hyperparameter":[44],"tuning":[45],"is":[46,181],"nontrivial":[47],"and":[48,58,70,80,129,148,167,199,210,213],"importantly,":[49],"lose":[51],"all":[52],"internal":[54],"information":[55],"about":[56],"pose":[57,79],"transformation":[59,81],"to":[60,104,109,116,125,190,226],"pooling.":[61],"Capsule":[62,146,155,168,179,197,202],"Networks":[63,121,189],"addressed":[65],"limitations":[67],"CNNs":[69],"great":[74],"by":[76,183],"calculating":[77],"image.":[84],"On":[85],"other":[87],"hand,":[88],"deeper":[89],"networks":[90,96],"are":[91],"more":[92,102],"powerful":[93],"than":[94],"shallow":[95],"but":[97],"at":[98],"same":[100],"time,":[101],"difficult":[103],"train.":[105],"Simply":[106],"adding":[107],"layers":[108],"make":[110],"network":[112],"deep":[113],"led":[115],"vanishing":[117],"gradient":[118],"problem.":[119],"Residual":[120,149,154,166,188],"introduce":[122],"skip":[123,184],"connections":[124,185],"ease":[126],"training":[128],"evidence":[132],"that":[133,159],"can":[135],"give":[136],"good":[137],"accuracy":[138],"considerable":[140],"depth.":[141],"Putting":[142],"best":[144,162],"together,":[151],"we":[152],"present":[153],"Network,":[156],"framework":[158],"uses":[160],"features":[163],"both":[165],"Networks.":[169],"In":[170],"proposed":[172],"model,":[173],"conventional":[175],"Convolutional":[176],"layer":[177],"replaced":[182],"like":[186],"decrease":[191,218],"complexity":[193],"Baseline":[196,228],"seven":[200],"ensemble":[201],"Network.":[203],"We":[204],"trained":[205],"our":[206],"model":[207],"on":[208],"MNIST":[209],"CIFAR-10":[211],"datasets":[212],"noted":[215],"significant":[217],"number":[221],"parameters":[223],"when":[224],"compared":[225],"models.":[229]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2021,"cited_by_count":7},{"year":2020,"cited_by_count":2}],"updated_date":"2026-07-02T09:51:11.867554","created_date":"2025-10-10T00:00:00"}
