{"id":"https://openalex.org/W4226365191","doi":"https://doi.org/10.1145/3507548.3507570","title":"Capsule Embedded ResNet for Image Classification","display_name":"Capsule Embedded ResNet for Image Classification","publication_year":2021,"publication_date":"2021-12-04","ids":{"openalex":"https://openalex.org/W4226365191","doi":"https://doi.org/10.1145/3507548.3507570"},"language":"en","primary_location":{"id":"doi:10.1145/3507548.3507570","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3507548.3507570","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 5th International Conference on Computer Science and Artificial Intelligence","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/A5100668786","display_name":"Weijie Liu","orcid":"https://orcid.org/0000-0002-8023-9913"},"institutions":[{"id":"https://openalex.org/I109935558","display_name":"Ningbo University","ror":"https://ror.org/03et85d35","country_code":"CN","type":"education","lineage":["https://openalex.org/I109935558"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Weijie Liu","raw_affiliation_strings":["Faculty of Electrical Engineering and Computer Science, Ningbo University, China"],"affiliations":[{"raw_affiliation_string":"Faculty of Electrical Engineering and Computer Science, Ningbo University, China","institution_ids":["https://openalex.org/I109935558"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100367140","display_name":"Weiwei Chen","orcid":"https://orcid.org/0000-0003-2845-1666"},"institutions":[{"id":"https://openalex.org/I109935558","display_name":"Ningbo University","ror":"https://ror.org/03et85d35","country_code":"CN","type":"education","lineage":["https://openalex.org/I109935558"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weiwei Chen","raw_affiliation_strings":["Faculty of Electrical Engineering and Computer Science, Ningbo University, China"],"affiliations":[{"raw_affiliation_string":"Faculty of Electrical Engineering and Computer Science, Ningbo University, China","institution_ids":["https://openalex.org/I109935558"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100769643","display_name":"Chong Wang","orcid":"https://orcid.org/0000-0001-6016-6545"},"institutions":[{"id":"https://openalex.org/I109935558","display_name":"Ningbo University","ror":"https://ror.org/03et85d35","country_code":"CN","type":"education","lineage":["https://openalex.org/I109935558"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chong Wang","raw_affiliation_strings":["Faculty of Electrical Engineering and Computer Science, Ningbo University, China"],"affiliations":[{"raw_affiliation_string":"Faculty of Electrical Engineering and Computer Science, Ningbo University, China","institution_ids":["https://openalex.org/I109935558"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053192405","display_name":"Qiaomei Mao","orcid":"https://orcid.org/0000-0002-0066-3758"},"institutions":[{"id":"https://openalex.org/I4210103986","display_name":"Jingdong (China)","ror":"https://ror.org/01dkjkq64","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210103986"]},{"id":"https://openalex.org/I109935558","display_name":"Ningbo University","ror":"https://ror.org/03et85d35","country_code":"CN","type":"education","lineage":["https://openalex.org/I109935558"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiaomei Mao","raw_affiliation_strings":["Faculty of Electrical Engineering and Computer Science, Ningbo University, China and Jingdong Logistics, China"],"affiliations":[{"raw_affiliation_string":"Faculty of Electrical Engineering and Computer Science, Ningbo University, China and Jingdong Logistics, China","institution_ids":["https://openalex.org/I109935558","https://openalex.org/I4210103986"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5062686002","display_name":"Xinmiao Dai","orcid":"https://orcid.org/0009-0009-4559-7641"},"institutions":[{"id":"https://openalex.org/I109935558","display_name":"Ningbo University","ror":"https://ror.org/03et85d35","country_code":"CN","type":"education","lineage":["https://openalex.org/I109935558"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinmiao Dai","raw_affiliation_strings":["Faculty of Electrical Engineering and Computer Science, Ningbo University, China"],"affiliations":[{"raw_affiliation_string":"Faculty of Electrical Engineering and Computer Science, Ningbo University, China","institution_ids":["https://openalex.org/I109935558"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5100668786"],"corresponding_institution_ids":["https://openalex.org/I109935558"],"apc_list":null,"apc_paid":null,"fwci":0.3843,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.62612745,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"143","last_page":"149"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9995999932289124,"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":0.9995999932289124,"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":0.996999979019165,"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/T12702","display_name":"Brain Tumor Detection and Classification","score":0.9943000078201294,"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":0.8001220226287842},{"id":"https://openalex.org/keywords/residual-neural-network","display_name":"Residual neural network","score":0.7733857035636902},{"id":"https://openalex.org/keywords/mnist-database","display_name":"MNIST database","score":0.744513750076294},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.727706789970398},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6987559795379639},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6336460709571838},{"id":"https://openalex.org/keywords/transformation","display_name":"Transformation (genetics)","score":0.5444437861442566},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.4951075613498688},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.4655027985572815},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.44257861375808716},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4278152585029602},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.413308322429657},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4034612774848938},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.31904077529907227},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.13529998064041138}],"concepts":[{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.8001220226287842},{"id":"https://openalex.org/C2944601119","wikidata":"https://www.wikidata.org/wiki/Q43744058","display_name":"Residual neural network","level":3,"score":0.7733857035636902},{"id":"https://openalex.org/C190502265","wikidata":"https://www.wikidata.org/wiki/Q17069496","display_name":"MNIST database","level":3,"score":0.744513750076294},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.727706789970398},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6987559795379639},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6336460709571838},{"id":"https://openalex.org/C204241405","wikidata":"https://www.wikidata.org/wiki/Q461499","display_name":"Transformation (genetics)","level":3,"score":0.5444437861442566},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.4951075613498688},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.4655027985572815},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.44257861375808716},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4278152585029602},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.413308322429657},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4034612774848938},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.31904077529907227},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.13529998064041138},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3507548.3507570","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3507548.3507570","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 5th International Conference on Computer Science and Artificial Intelligence","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W1483870316","https://openalex.org/W1686810756","https://openalex.org/W1832693441","https://openalex.org/W2097117768","https://openalex.org/W2147800946","https://openalex.org/W2163605009","https://openalex.org/W2194775991","https://openalex.org/W2549139847","https://openalex.org/W2797472209","https://openalex.org/W2903024257","https://openalex.org/W2913059114","https://openalex.org/W2942211779","https://openalex.org/W2944008497","https://openalex.org/W2944527105","https://openalex.org/W2963037989","https://openalex.org/W2963446712","https://openalex.org/W2967177870","https://openalex.org/W2982147654","https://openalex.org/W3149348938","https://openalex.org/W4212774754","https://openalex.org/W6743446608","https://openalex.org/W6750207810","https://openalex.org/W6768246183","https://openalex.org/W6773495315"],"related_works":["https://openalex.org/W3177008965","https://openalex.org/W2947175736","https://openalex.org/W2167735388","https://openalex.org/W4309224979","https://openalex.org/W2995715801","https://openalex.org/W3156786002","https://openalex.org/W4317374280","https://openalex.org/W3089733734","https://openalex.org/W2732542196","https://openalex.org/W564581980"],"abstract_inverted_index":{"Various":[0],"neural":[1,15,27,33],"network":[2,16,34],"models":[3,24],"have":[4],"been":[5],"proposed":[6,60,68,127],"in":[7,48,98],"the":[8,13,21,31,40,49,63,71,85,95,120,124,126,144,148],"past":[9],"decade.":[10],"Among":[11],"them,":[12],"residual":[14],"(ResNet)":[17],"is":[18,36,59,115],"one":[19],"of":[20,25,46,65],"most":[22],"successful":[23],"convolutional":[26,75,111],"networks":[28],"(CNNs),":[29],"while":[30,87],"capsule":[32,55,89],"(CapsNet)":[35],"more":[37],"robust":[38],"to":[39,61,77,80,93,100,118],"rotation,":[41],"translation":[42],"and":[43,113,131,136],"other":[44],"transformations":[45],"objects":[47],"images.":[50],"In":[51,123],"this":[52],"paper,":[53],"a":[54,102],"embedded":[56,92],"ResNet":[57,72,150],"(CE-ResNet)":[58],"combine":[62],"strengths":[64],"both.":[66],"The":[67,108],"CE-ResNet":[69],"utilizes":[70],"blocks":[73],"based":[74],"layers":[76,90,112],"extract":[78],"low":[79],"medium":[81],"level":[82],"features":[83],"from":[84],"images,":[86],"two":[88],"are":[91,141],"process":[94],"high-level":[96],"information":[97],"order":[99],"provide":[101],"better":[103],"performance":[104],"for":[105],"image":[106],"classification.":[107],"transformation":[109],"between":[110],"capsules":[114,121],"carefully":[116],"designed":[117],"embed":[119],"properly.":[122],"experiments,":[125],"model":[128],"achieves":[129],"90.8%":[130],"99.64%":[132],"accuracies":[133,145],"on":[134],"CIFAR-10":[135],"MNIST":[137],"datasets":[138],"respectively,":[139],"which":[140],"higher":[142],"than":[143],"reported":[146],"by":[147],"vanilla":[149],"or":[151],"CapsNet.":[152]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"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"}
