{"id":"https://openalex.org/W3163392018","doi":"https://doi.org/10.1109/ijcnn52387.2021.9534076","title":"One for All: An End-to-End Compact Solution for Hand Gesture Recognition","display_name":"One for All: An End-to-End Compact Solution for Hand Gesture Recognition","publication_year":2021,"publication_date":"2021-07-18","ids":{"openalex":"https://openalex.org/W3163392018","doi":"https://doi.org/10.1109/ijcnn52387.2021.9534076","mag":"3163392018"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn52387.2021.9534076","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn52387.2021.9534076","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2105.07143","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5035047633","display_name":"Monu Verma","orcid":"https://orcid.org/0000-0003-4962-882X"},"institutions":[{"id":"https://openalex.org/I83205935","display_name":"Malaviya National Institute of Technology Jaipur","ror":"https://ror.org/0077k1j32","country_code":"IN","type":"education","lineage":["https://openalex.org/I83205935"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Monu Verma","raw_affiliation_strings":["Malaviya National Institute of Technology,Computer Science and Engineering,Jaipur,India,302017"],"affiliations":[{"raw_affiliation_string":"Malaviya National Institute of Technology,Computer Science and Engineering,Jaipur,India,302017","institution_ids":["https://openalex.org/I83205935"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085689963","display_name":"Ayushi Gupta","orcid":"https://orcid.org/0000-0001-6048-8069"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ayushi Gupta","raw_affiliation_strings":["Olx people,Bangalore,Karnataka,560034"],"affiliations":[{"raw_affiliation_string":"Olx people,Bangalore,Karnataka,560034","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5015414891","display_name":"Santosh Kumar Vipparthi","orcid":"https://orcid.org/0000-0002-5672-3537"},"institutions":[{"id":"https://openalex.org/I83205935","display_name":"Malaviya National Institute of Technology Jaipur","ror":"https://ror.org/0077k1j32","country_code":"IN","type":"education","lineage":["https://openalex.org/I83205935"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Santosh K. Vipparthi","raw_affiliation_strings":["Malaviya National Institute of Technology,Computer Science and Engineering,Jaipur,India,302017","MALAVIYA NATIONAL INSTITUTE OF TECHNOLOGY JAIPUR"],"affiliations":[{"raw_affiliation_string":"Malaviya National Institute of Technology,Computer Science and Engineering,Jaipur,India,302017","institution_ids":["https://openalex.org/I83205935"]},{"raw_affiliation_string":"MALAVIYA NATIONAL INSTITUTE OF TECHNOLOGY JAIPUR","institution_ids":["https://openalex.org/I83205935"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5035047633"],"corresponding_institution_ids":["https://openalex.org/I83205935"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.04318591,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"171","issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11398","display_name":"Hand Gesture Recognition Systems","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"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/T11398","display_name":"Hand Gesture Recognition Systems","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9926000237464905,"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/T12740","display_name":"Gait Recognition and Analysis","score":0.9884999990463257,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7780225872993469},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.7009905576705933},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.643319845199585},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6264005303382874},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5929803848266602},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5783995389938354},{"id":"https://openalex.org/keywords/gesture","display_name":"Gesture","score":0.5435441136360168},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5262212753295898},{"id":"https://openalex.org/keywords/end-to-end-principle","display_name":"End-to-end principle","score":0.5252974629402161},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.49629098176956177},{"id":"https://openalex.org/keywords/layer","display_name":"Layer (electronics)","score":0.4931918978691101},{"id":"https://openalex.org/keywords/gesture-recognition","display_name":"Gesture recognition","score":0.47353312373161316},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.4610613286495209},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.45009782910346985},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.4400605857372284},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.32932284474372864},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.18994447588920593},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.08362400531768799},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.06999647617340088}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7780225872993469},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.7009905576705933},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.643319845199585},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6264005303382874},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5929803848266602},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5783995389938354},{"id":"https://openalex.org/C207347870","wikidata":"https://www.wikidata.org/wiki/Q371174","display_name":"Gesture","level":2,"score":0.5435441136360168},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5262212753295898},{"id":"https://openalex.org/C74296488","wikidata":"https://www.wikidata.org/wiki/Q2527392","display_name":"End-to-end principle","level":2,"score":0.5252974629402161},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.49629098176956177},{"id":"https://openalex.org/C2779227376","wikidata":"https://www.wikidata.org/wiki/Q6505497","display_name":"Layer (electronics)","level":2,"score":0.4931918978691101},{"id":"https://openalex.org/C159437735","wikidata":"https://www.wikidata.org/wiki/Q1519524","display_name":"Gesture recognition","level":3,"score":0.47353312373161316},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.4610613286495209},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.45009782910346985},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.4400605857372284},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.32932284474372864},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.18994447588920593},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08362400531768799},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.06999647617340088},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"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/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"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/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"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/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/ijcnn52387.2021.9534076","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn52387.2021.9534076","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2105.07143","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2105.07143","pdf_url":"https://arxiv.org/pdf/2105.07143","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":null},{"id":"mag:3163392018","is_oa":true,"landing_page_url":"http://export.arxiv.org/pdf/2105.07143","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.2105.07143","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2105.07143","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2105.07143","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2105.07143","pdf_url":"https://arxiv.org/pdf/2105.07143","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":null},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.5699999928474426}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3163392018.pdf","grobid_xml":"https://content.openalex.org/works/W3163392018.grobid-xml"},"referenced_works_count":47,"referenced_works":["https://openalex.org/W1542385370","https://openalex.org/W1635989058","https://openalex.org/W1686810756","https://openalex.org/W1980601381","https://openalex.org/W1993928670","https://openalex.org/W2028471190","https://openalex.org/W2113819043","https://openalex.org/W2138672819","https://openalex.org/W2139670260","https://openalex.org/W2183341477","https://openalex.org/W2194775991","https://openalex.org/W2274287116","https://openalex.org/W2318145034","https://openalex.org/W2562399047","https://openalex.org/W2576349173","https://openalex.org/W2612445135","https://openalex.org/W2765785234","https://openalex.org/W2771579111","https://openalex.org/W2772312976","https://openalex.org/W2885190481","https://openalex.org/W2888924343","https://openalex.org/W2894027118","https://openalex.org/W2894913190","https://openalex.org/W2919504802","https://openalex.org/W2938266529","https://openalex.org/W2955948662","https://openalex.org/W2962067162","https://openalex.org/W2962879438","https://openalex.org/W2963163009","https://openalex.org/W2963446712","https://openalex.org/W2963840672","https://openalex.org/W2964081807","https://openalex.org/W2964139520","https://openalex.org/W2973305447","https://openalex.org/W2975768142","https://openalex.org/W2980289721","https://openalex.org/W2998948697","https://openalex.org/W3013985383","https://openalex.org/W3033852812","https://openalex.org/W3100728255","https://openalex.org/W3117417827","https://openalex.org/W6637373629","https://openalex.org/W6694260854","https://openalex.org/W6696085341","https://openalex.org/W6737664043","https://openalex.org/W6761120048","https://openalex.org/W6788347070"],"related_works":["https://openalex.org/W3186153124","https://openalex.org/W2941372268","https://openalex.org/W3211758342","https://openalex.org/W2982401466","https://openalex.org/W2801610476","https://openalex.org/W1751494390","https://openalex.org/W3118546327","https://openalex.org/W2590173477","https://openalex.org/W3025294541","https://openalex.org/W3118503254","https://openalex.org/W3117417827","https://openalex.org/W2510373542","https://openalex.org/W3004450906","https://openalex.org/W2970908668","https://openalex.org/W2607976391","https://openalex.org/W3151904266","https://openalex.org/W2765431248","https://openalex.org/W3197089899","https://openalex.org/W3191283664","https://openalex.org/W3093534379"],"abstract_inverted_index":{"The":[0,24,49,100,118,134,197],"HGR":[1,29],"is":[2,10,137,169,202],"a":[3,161],"quite":[4],"challenging":[5],"task":[6],"as":[7,16,55,57,97],"its":[8],"performance":[9],"influenced":[11],"by":[12,126,143,189,204],"various":[13,39],"aspects":[14],"such":[15],"illumination":[17,43],"variations,":[18,44],"cluttered":[19,47],"backgrounds,":[20],"spontaneous":[21],"capture,":[22],"etc.":[23],"conventional":[25],"CNN":[26,81],"networks":[27],"for":[28,88],"are":[30],"following":[31],"two":[32,108],"stage":[33,61],"pipeline":[34,101],"to":[35,63,93,139,172,230],"deal":[36],"with":[37],"the":[38,65,68,95,103,145,174,184,187,232,236],"challenges:":[40],"complex":[41,45],"signs,":[42],"and":[46,113,179,209,226],"backgrounds.":[48],"existing":[50],"approaches":[51],"needs":[52],"expert":[53],"expertise":[54],"well":[56],"auxiliary":[58],"computation":[59],"at":[60],"1":[62],"remove":[64],"complexities":[66],"from":[67],"input":[69],"images.":[70],"Therefore,":[71],"in":[72],"this":[73],"paper,":[74],"we":[75,240],"proposes":[76],"an":[77],"novel":[78],"end-to-end":[79],"compact":[80],"framework:":[82],"fine":[83,122],"grained":[84,123],"feature":[85,124],"attentive":[86],"network":[87,188],"hand":[89,158,195],"gesture":[90],"recognition":[91],"(Fit-Hand)":[92],"solve":[94],"challenges":[96],"discussed":[98],"above.":[99],"of":[102,107,148,157,176,186,194,199,235],"proposed":[104,237],"architecture":[105],"consists":[106],"main":[109],"units:":[110],"FineFeat":[111,119,177],"module":[112,120,178],"dilated":[114,152,180],"convolutional":[115],"(Conv)":[116],"layer.":[117],"extracts":[121],"maps":[125],"employing":[127],"attention":[128,135],"mechanism":[129,136],"over":[130,215],"multiscale":[131],"receptive":[132,163],"fields.":[133],"introduced":[138],"capture":[140],"effective":[141],"features":[142,156,175],"enlarging":[144],"average":[146],"behaviour":[147],"multi-scale":[149],"responses.":[150],"Moreover,":[151],"convolution":[153],"provides":[154],"global":[155],"gestures":[159],"through":[160],"larger":[162],"field.":[164],"In":[165],"addition,":[166],"integrated":[167],"layer":[168,181],"also":[170],"utilized":[171],"combine":[173],"which":[182],"enhances":[183],"discriminability":[185],"capturing":[190],"complementary":[191],"context":[192],"information":[193],"postures.":[196],"effectiveness":[198],"Fit-":[200],"Hand":[201],"evaluated":[203],"using":[205],"subject":[206,210],"dependent":[207],"(SD)":[208],"independent":[211],"(SI)":[212],"validation":[213],"setup":[214],"seven":[216],"benchmark":[217],"datasets:":[218],"MUGD-I,":[219],"MUGD-II,":[220],"MUGD-III,":[221],"MUGD-IV,":[222],"MUGD-V,":[223],"Finger":[224],"Spelling":[225],"OUHANDS,":[227],"respectively.":[228],"Furthermore,":[229],"investigate":[231],"deep":[233],"insights":[234],"Fit-Hand":[238],"framework,":[239],"performed":[241],"ten":[242],"ablation":[243],"study.":[244]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}