{"id":"https://openalex.org/W3089378201","doi":"https://doi.org/10.1109/ijcnn48605.2020.9206785","title":"A Light-weight Deep Feature based Capsule Network","display_name":"A Light-weight Deep Feature based Capsule Network","publication_year":2020,"publication_date":"2020-07-01","ids":{"openalex":"https://openalex.org/W3089378201","doi":"https://doi.org/10.1109/ijcnn48605.2020.9206785","mag":"3089378201"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn48605.2020.9206785","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn48605.2020.9206785","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/A5101746471","display_name":"Chandan Kumar Singh","orcid":"https://orcid.org/0000-0001-9566-4309"},"institutions":[{"id":"https://openalex.org/I55215948","display_name":"Tata Consultancy Services (India)","ror":"https://ror.org/01b9n8m42","country_code":"IN","type":"company","lineage":["https://openalex.org/I4210086519","https://openalex.org/I55215948"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Chandan Kumar Singh","raw_affiliation_strings":["Researchers at TCS Innovation Labs, India"],"affiliations":[{"raw_affiliation_string":"Researchers at TCS Innovation Labs, India","institution_ids":["https://openalex.org/I55215948"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034836914","display_name":"Vivek Gangwar","orcid":"https://orcid.org/0009-0008-7206-7294"},"institutions":[{"id":"https://openalex.org/I55215948","display_name":"Tata Consultancy Services (India)","ror":"https://ror.org/01b9n8m42","country_code":"IN","type":"company","lineage":["https://openalex.org/I4210086519","https://openalex.org/I55215948"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Vivek Kumar Gangwar","raw_affiliation_strings":["Researchers at TCS Innovation Labs, India"],"affiliations":[{"raw_affiliation_string":"Researchers at TCS Innovation Labs, India","institution_ids":["https://openalex.org/I55215948"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009996322","display_name":"Anima Majumder","orcid":"https://orcid.org/0000-0002-6300-010X"},"institutions":[{"id":"https://openalex.org/I55215948","display_name":"Tata Consultancy Services (India)","ror":"https://ror.org/01b9n8m42","country_code":"IN","type":"company","lineage":["https://openalex.org/I4210086519","https://openalex.org/I55215948"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Anima Majumder","raw_affiliation_strings":["Researchers at TCS Innovation Labs, India"],"affiliations":[{"raw_affiliation_string":"Researchers at TCS Innovation Labs, India","institution_ids":["https://openalex.org/I55215948"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053838336","display_name":"Swagat Kumar","orcid":"https://orcid.org/0000-0001-7405-3445"},"institutions":[{"id":"https://openalex.org/I55215948","display_name":"Tata Consultancy Services (India)","ror":"https://ror.org/01b9n8m42","country_code":"IN","type":"company","lineage":["https://openalex.org/I4210086519","https://openalex.org/I55215948"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Swagat Kumar","raw_affiliation_strings":["Researchers at TCS Innovation Labs, India"],"affiliations":[{"raw_affiliation_string":"Researchers at TCS Innovation Labs, India","institution_ids":["https://openalex.org/I55215948"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083217233","display_name":"Prakash Chanderlal Ambwani","orcid":null},"institutions":[{"id":"https://openalex.org/I55215948","display_name":"Tata Consultancy Services (India)","ror":"https://ror.org/01b9n8m42","country_code":"IN","type":"company","lineage":["https://openalex.org/I4210086519","https://openalex.org/I55215948"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Prakash Chanderlal Ambwani","raw_affiliation_strings":["Researchers at TCS Innovation Labs, India"],"affiliations":[{"raw_affiliation_string":"Researchers at TCS Innovation Labs, India","institution_ids":["https://openalex.org/I55215948"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5061262677","display_name":"Rajesh Kumar Sinha","orcid":"https://orcid.org/0000-0002-0428-8457"},"institutions":[{"id":"https://openalex.org/I55215948","display_name":"Tata Consultancy Services (India)","ror":"https://ror.org/01b9n8m42","country_code":"IN","type":"company","lineage":["https://openalex.org/I4210086519","https://openalex.org/I55215948"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Rajesh Sinha","raw_affiliation_strings":["Researchers at TCS Innovation Labs, India"],"affiliations":[{"raw_affiliation_string":"Researchers at TCS Innovation Labs, India","institution_ids":["https://openalex.org/I55215948"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5101746471"],"corresponding_institution_ids":["https://openalex.org/I55215948"],"apc_list":null,"apc_paid":null,"fwci":0.3908,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.62072326,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10601","display_name":"Handwritten Text Recognition 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/T10601","display_name":"Handwritten Text Recognition 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":0.9984999895095825,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9968000054359436,"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":0.8020118474960327},{"id":"https://openalex.org/keywords/normalization","display_name":"Normalization (sociology)","score":0.5978662967681885},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5954302549362183},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.5474269986152649},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5373979806900024},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5338500738143921},{"id":"https://openalex.org/keywords/mnist-database","display_name":"MNIST database","score":0.5100055932998657},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4887959659099579},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.48625457286834717},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4862169325351715},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.2801865339279175}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8020118474960327},{"id":"https://openalex.org/C136886441","wikidata":"https://www.wikidata.org/wiki/Q926129","display_name":"Normalization (sociology)","level":2,"score":0.5978662967681885},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5954302549362183},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.5474269986152649},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5373979806900024},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5338500738143921},{"id":"https://openalex.org/C190502265","wikidata":"https://www.wikidata.org/wiki/Q17069496","display_name":"MNIST database","level":3,"score":0.5100055932998657},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4887959659099579},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.48625457286834717},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4862169325351715},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2801865339279175},{"id":"https://openalex.org/C19165224","wikidata":"https://www.wikidata.org/wiki/Q23404","display_name":"Anthropology","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn48605.2020.9206785","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn48605.2020.9206785","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":[{"id":"https://metadata.un.org/sdg/9","score":0.5,"display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":40,"referenced_works":["https://openalex.org/W2966661","https://openalex.org/W1686810756","https://openalex.org/W2163605009","https://openalex.org/W2194775991","https://openalex.org/W2274287116","https://openalex.org/W2335728318","https://openalex.org/W2750384547","https://openalex.org/W2775143585","https://openalex.org/W2785994986","https://openalex.org/W2797275157","https://openalex.org/W2803603832","https://openalex.org/W2803948231","https://openalex.org/W2895526696","https://openalex.org/W2902319695","https://openalex.org/W2917233393","https://openalex.org/W2963143796","https://openalex.org/W2963703618","https://openalex.org/W2964318666","https://openalex.org/W2964350391","https://openalex.org/W2978989174","https://openalex.org/W3118608800","https://openalex.org/W4295094398","https://openalex.org/W4295238618","https://openalex.org/W6600115225","https://openalex.org/W6637373629","https://openalex.org/W6684191040","https://openalex.org/W6694260854","https://openalex.org/W6703116779","https://openalex.org/W6743446608","https://openalex.org/W6743688258","https://openalex.org/W6747050675","https://openalex.org/W6748053814","https://openalex.org/W6748823286","https://openalex.org/W6750618652","https://openalex.org/W6751741970","https://openalex.org/W6751830424","https://openalex.org/W6751928294","https://openalex.org/W6756796901","https://openalex.org/W6759721166","https://openalex.org/W6787972765"],"related_works":["https://openalex.org/W4386603768","https://openalex.org/W2950475743","https://openalex.org/W2886711096","https://openalex.org/W3034421924","https://openalex.org/W4386858688","https://openalex.org/W2982536526","https://openalex.org/W4380302312","https://openalex.org/W3008689640","https://openalex.org/W4385338604","https://openalex.org/W3081626085"],"abstract_inverted_index":{"Capsule":[0,70],"Network":[1],"(CapsNet)":[2],"has":[3,176,214],"motivated":[4],"researchers":[5],"to":[6,11,123,208,222],"work":[7],"on":[8,152],"it":[9],"due":[10],"its":[12,23,30,49],"distinct":[13],"capability":[14],"of":[15,29,69,89,92,131,141,165,219,224,237],"retaining":[16],"spatial":[17],"correlations":[18],"between":[19,203],"image":[20],"features.":[21],"However,":[22],"applicability":[24],"is":[25,145,227,232],"still":[26],"limited":[27],"because":[28],"intensive":[31],"computational":[32],"cost,":[33],"memory":[34],"usage":[35],"and":[36,72,107,160,242],"bandwidth":[37],"requirement.":[38],"This":[39,231],"paper":[40],"proposes":[41],"a":[42,73,90,98,110],"computationally":[43,136],"efficient,":[44],"lightweight":[45,212],"CapsNet":[46],"which":[47,162,226],"paves":[48],"way":[50],"forward":[51],"for":[52,81],"deployment":[53],"in":[54,61,246],"constrained":[55],"edge":[56],"devices":[57],"as":[58,60,78,156,168,170,206],"well":[59,169],"web":[62],"based":[63],"applications.":[64],"The":[65,83,115,139,185,210],"proposed":[66,143,193,211],"framework":[67,144],"consists":[68],"layers":[71],"deep":[74,84,196,238],"feature":[75,85,93,239],"representation":[76,86],"layer":[77,87],"an":[79],"input":[80,120,197],"capsules.":[82],"comprises":[88],"series":[91],"blocks,":[94],"containing":[95],"convolution":[96,108],"with":[97,109,128,180,187,195],"3":[99,101],"\u00d7":[100,112],"kernel":[102],"followed":[103],"by":[104,147,234],"batch":[105],"normalization":[106],"1":[111,113],"kernel.":[114],"deeper":[116],"or":[117],"better":[118],"represented":[119],"features":[121,198],"help":[122],"improve":[124],"recognition":[125,188],"performance":[126],"even":[127],"lesser":[129],"number":[130,218],"capsules,":[132],"making":[133],"the":[134,142,181,192,204,217,247],"network":[135,213],"more":[137,200],"efficient.":[138],"efficacy":[140],"validated":[146],"performing":[148],"rigorous":[149],"experimental":[150],"studies":[151],"different":[153],"datasets,":[154],"such":[155],"CIFAR-10,":[157],"FMNIST,":[158],"MNIST":[159],"SVHN":[161],"include":[163],"images":[164],"object":[166],"classes":[167],"text":[171],"characters.":[172],"A":[173],"comparative":[174],"analysis":[175],"also":[177],"been":[178],"done":[179],"state-of-the-art":[182],"technique":[183],"CapsNet.":[184,209],"comparison":[186],"accuracy":[189],"ensures":[190],"that,":[191],"architecture":[194],"provides":[199],"efficient":[201],"routing":[202],"capsules":[205],"compared":[207],"scaled":[215],"down":[216],"parameters":[220],"up":[221],"60%":[223],"CapsNet,":[225],"another":[228],"significant":[229],"contribution.":[230],"achieved":[233],"collaborative":[235],"effect":[236],"generation":[240],"module":[241],"parametric":[243],"changes":[244],"performed":[245],"primary":[248],"capsule":[249],"layer.":[250]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}