{"id":"https://openalex.org/W3128842017","doi":"https://doi.org/10.1145/3441110.3441148","title":"Convolutional Fully-Connected Capsule Network (CFC-CapsNet)","display_name":"Convolutional Fully-Connected Capsule Network (CFC-CapsNet)","publication_year":2021,"publication_date":"2021-01-18","ids":{"openalex":"https://openalex.org/W3128842017","doi":"https://doi.org/10.1145/3441110.3441148","mag":"3128842017"},"language":"en","primary_location":{"id":"doi:10.1145/3441110.3441148","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3441110.3441148","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Workshop on Design and Architectures for Signal and Image Processing (14th edition)","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/A5052700161","display_name":"Pouya Shiri","orcid":"https://orcid.org/0000-0002-8037-9481"},"institutions":[{"id":"https://openalex.org/I212119943","display_name":"University of Victoria","ror":"https://ror.org/04s5mat29","country_code":"CA","type":"education","lineage":["https://openalex.org/I212119943"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"Pouya Shiri","raw_affiliation_strings":["University of Victoria, Canada"],"affiliations":[{"raw_affiliation_string":"University of Victoria, Canada","institution_ids":["https://openalex.org/I212119943"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5000153604","display_name":"Amirali Baniasadi","orcid":null},"institutions":[{"id":"https://openalex.org/I212119943","display_name":"University of Victoria","ror":"https://ror.org/04s5mat29","country_code":"CA","type":"education","lineage":["https://openalex.org/I212119943"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Amirali Baniasadi","raw_affiliation_strings":["University of Victoria, Canada"],"affiliations":[{"raw_affiliation_string":"University of Victoria, Canada","institution_ids":["https://openalex.org/I212119943"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5052700161"],"corresponding_institution_ids":["https://openalex.org/I212119943"],"apc_list":null,"apc_paid":null,"fwci":0.9607,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.76586601,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"19","last_page":"25"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9998999834060669,"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":0.9998999834060669,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9986000061035156,"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/T12702","display_name":"Brain Tumor Detection and Classification","score":0.9979000091552734,"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/convolutional-neural-network","display_name":"Convolutional neural network","score":0.8135097026824951},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7962687015533447},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.7545838356018066},{"id":"https://openalex.org/keywords/mnist-database","display_name":"MNIST database","score":0.7502090334892273},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6339209675788879},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5979593992233276},{"id":"https://openalex.org/keywords/affine-transformation","display_name":"Affine transformation","score":0.5880842208862305},{"id":"https://openalex.org/keywords/convolutional-code","display_name":"Convolutional code","score":0.55260169506073},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5136932730674744},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.25867074728012085},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.22065094113349915},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.07492029666900635}],"concepts":[{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.8135097026824951},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7962687015533447},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.7545838356018066},{"id":"https://openalex.org/C190502265","wikidata":"https://www.wikidata.org/wiki/Q17069496","display_name":"MNIST database","level":3,"score":0.7502090334892273},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6339209675788879},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5979593992233276},{"id":"https://openalex.org/C92757383","wikidata":"https://www.wikidata.org/wiki/Q382497","display_name":"Affine transformation","level":2,"score":0.5880842208862305},{"id":"https://openalex.org/C157899210","wikidata":"https://www.wikidata.org/wiki/Q1395022","display_name":"Convolutional code","level":3,"score":0.55260169506073},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5136932730674744},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.25867074728012085},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.22065094113349915},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.07492029666900635},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","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/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3441110.3441148","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3441110.3441148","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Workshop on Design and Architectures for Signal and Image Processing (14th edition)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W2805939409","https://openalex.org/W2895526696","https://openalex.org/W2947430673","https://openalex.org/W2965481041","https://openalex.org/W3027282947","https://openalex.org/W3028488836","https://openalex.org/W3098854735","https://openalex.org/W3101197104"],"related_works":["https://openalex.org/W4386603768","https://openalex.org/W2950475743","https://openalex.org/W3036048022","https://openalex.org/W4309224979","https://openalex.org/W3026879719","https://openalex.org/W4226493464","https://openalex.org/W3133861977","https://openalex.org/W2951211570","https://openalex.org/W3103566983","https://openalex.org/W3029198973"],"abstract_inverted_index":{"Capsule":[0],"Networks":[1,45],"(CapsNets)":[2],"are":[3,52,85],"the":[4,13,36,97],"new":[5],"generation":[6],"of":[7,27,113],"classifiers":[8],"with":[9],"several":[10],"advantages":[11,17],"over":[12],"previous":[14],"ones.":[15],"Such":[16],"include":[18],"higher":[19,91],"robustness":[20],"to":[21,55,72,96],"affine":[22],"transformed":[23],"datasets":[24],"and":[25,83,88,106],"detection":[26],"overlapping":[28],"images.":[29],"CapsNets,":[30],"while":[31],"obtaining":[32],"state-of-the-art":[33],"accuracy":[34,92],"on":[35,122],"MNIST":[37],"digit":[38],"recognition":[39],"dataset,":[40],"fall":[41],"behind":[42],"Convolutional":[43,62],"Neural":[44],"(CNNs)":[46],"for":[47,118],"other":[48],"datasets.":[49],"Moreover,":[50],"CapsNets":[51],"slow":[53],"compared":[54,95],"CNNs.":[56],"In":[57],"this":[58],"work,":[59],"we":[60],"propose":[61],"Fully":[63],"Connected":[64],"(CFC)":[65],"CapsNet":[66,74],"as":[67],"an":[68],"alternative":[69],"enhanced":[70],"architecture":[71],"conventional":[73,98],"[8].":[75],"CFC-CapsNet":[76,100,119],"is":[77,93,108,120],"a":[78,89],"more":[79,109],"efficient":[80,110],"network:":[81],"training":[82],"testing":[84],"performed":[86],"faster":[87],"slightly":[90],"achieved":[94],"CapsNet.":[99],"includes":[101],"fewer":[102],"trainable":[103],"weights":[104],"(parameters)":[105],"therefore":[107],"in":[111],"terms":[112],"memory":[114],"usage.":[115],"The":[116],"code":[117],"available":[121],"Github":[123],"1.":[124]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
