{"id":"https://openalex.org/W4396988544","doi":"https://doi.org/10.1145/3639856.3639874","title":"Binary Convolutional Neural Network for Efficient Gesture Recognition at Edge","display_name":"Binary Convolutional Neural Network for Efficient Gesture Recognition at Edge","publication_year":2023,"publication_date":"2023-10-25","ids":{"openalex":"https://openalex.org/W4396988544","doi":"https://doi.org/10.1145/3639856.3639874"},"language":"en","primary_location":{"id":"doi:10.1145/3639856.3639874","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3639856.3639874","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3639856.3639874","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Third International Conference on AI-ML Systems","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3639856.3639874","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5031675991","display_name":"Jayeeta Mondal","orcid":"https://orcid.org/0000-0002-8809-494X"},"institutions":[{"id":"https://openalex.org/I4210145666","display_name":"Embedded Systems (United States)","ror":"https://ror.org/04742eh45","country_code":"US","type":"company","lineage":["https://openalex.org/I4210145666"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jayeeta Mondal","raw_affiliation_strings":["Embedded Devices &amp; Intelligent Systems, TCS Research, IN"],"raw_orcid":"https://orcid.org/0000-0002-8809-494X","affiliations":[{"raw_affiliation_string":"Embedded Devices &amp; Intelligent Systems, TCS Research, IN","institution_ids":["https://openalex.org/I4210145666"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025308099","display_name":"S. Dey","orcid":null},"institutions":[{"id":"https://openalex.org/I4210145666","display_name":"Embedded Systems (United States)","ror":"https://ror.org/04742eh45","country_code":"US","type":"company","lineage":["https://openalex.org/I4210145666"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Swarnava Dey","raw_affiliation_strings":["Embedded Devices &amp; Intelligent Systems, TCS Research, Tata Consultancy Services Ltd., IN"],"raw_orcid":"https://orcid.org/0000-0002-3988-1445","affiliations":[{"raw_affiliation_string":"Embedded Devices &amp; Intelligent Systems, TCS Research, Tata Consultancy Services Ltd., IN","institution_ids":["https://openalex.org/I4210145666"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5031139197","display_name":"Arijit Mukherjee","orcid":"https://orcid.org/0000-0001-5052-4476"},"institutions":[{"id":"https://openalex.org/I4210145666","display_name":"Embedded Systems (United States)","ror":"https://ror.org/04742eh45","country_code":"US","type":"company","lineage":["https://openalex.org/I4210145666"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Arijit Mukherjee","raw_affiliation_strings":["Embedded Devices &amp; Intelligent Systems, TCS Research, IN"],"raw_orcid":"https://orcid.org/0000-0001-5052-4476","affiliations":[{"raw_affiliation_string":"Embedded Devices &amp; Intelligent Systems, TCS Research, IN","institution_ids":["https://openalex.org/I4210145666"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210145666"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.25369537,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"10"},"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/T10914","display_name":"Tactile and Sensory Interactions","score":0.9943000078201294,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11285","display_name":"Hearing Impairment and Communication","score":0.9923999905586243,"subfield":{"id":"https://openalex.org/subfields/3204","display_name":"Developmental and Educational Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8388991355895996},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.8157433271408081},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6688280701637268},{"id":"https://openalex.org/keywords/gesture-recognition","display_name":"Gesture recognition","score":0.6208429932594299},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5845926403999329},{"id":"https://openalex.org/keywords/edge-device","display_name":"Edge device","score":0.5667117834091187},{"id":"https://openalex.org/keywords/gesture","display_name":"Gesture","score":0.5203575491905212},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4809652864933014},{"id":"https://openalex.org/keywords/edge-computing","display_name":"Edge computing","score":0.447057843208313},{"id":"https://openalex.org/keywords/mobile-device","display_name":"Mobile device","score":0.44660335779190063},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.4446125626564026},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.43473032116889954},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.34939032793045044},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.33843788504600525},{"id":"https://openalex.org/keywords/cloud-computing","display_name":"Cloud computing","score":0.10110825300216675}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8388991355895996},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.8157433271408081},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6688280701637268},{"id":"https://openalex.org/C159437735","wikidata":"https://www.wikidata.org/wiki/Q1519524","display_name":"Gesture recognition","level":3,"score":0.6208429932594299},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5845926403999329},{"id":"https://openalex.org/C138236772","wikidata":"https://www.wikidata.org/wiki/Q25098575","display_name":"Edge device","level":3,"score":0.5667117834091187},{"id":"https://openalex.org/C207347870","wikidata":"https://www.wikidata.org/wiki/Q371174","display_name":"Gesture","level":2,"score":0.5203575491905212},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4809652864933014},{"id":"https://openalex.org/C2778456923","wikidata":"https://www.wikidata.org/wiki/Q5337692","display_name":"Edge computing","level":3,"score":0.447057843208313},{"id":"https://openalex.org/C186967261","wikidata":"https://www.wikidata.org/wiki/Q5082128","display_name":"Mobile device","level":2,"score":0.44660335779190063},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.4446125626564026},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.43473032116889954},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.34939032793045044},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.33843788504600525},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.10110825300216675},{"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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3639856.3639874","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3639856.3639874","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3639856.3639874","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Third International Conference on AI-ML Systems","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3639856.3639874","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3639856.3639874","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3639856.3639874","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Third International Conference on AI-ML Systems","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4396988544.pdf","grobid_xml":"https://content.openalex.org/works/W4396988544.grobid-xml"},"referenced_works_count":36,"referenced_works":["https://openalex.org/W1965893768","https://openalex.org/W1980601381","https://openalex.org/W2005496958","https://openalex.org/W2020243185","https://openalex.org/W2055816619","https://openalex.org/W2074772891","https://openalex.org/W2090411045","https://openalex.org/W2108598243","https://openalex.org/W2124659975","https://openalex.org/W2134719325","https://openalex.org/W2138988042","https://openalex.org/W2194775991","https://openalex.org/W2300242332","https://openalex.org/W2538825097","https://openalex.org/W2549139847","https://openalex.org/W2752782242","https://openalex.org/W2770887258","https://openalex.org/W2883780447","https://openalex.org/W2887447938","https://openalex.org/W2913362834","https://openalex.org/W2922509574","https://openalex.org/W2963125010","https://openalex.org/W2963446712","https://openalex.org/W2965112580","https://openalex.org/W2973305447","https://openalex.org/W2999803881","https://openalex.org/W3004061291","https://openalex.org/W3013985383","https://openalex.org/W3042011474","https://openalex.org/W3042939502","https://openalex.org/W3139490795","https://openalex.org/W3175878110","https://openalex.org/W4246799907","https://openalex.org/W4288083474","https://openalex.org/W4301409532","https://openalex.org/W6770599708"],"related_works":["https://openalex.org/W2902873204","https://openalex.org/W2185750513","https://openalex.org/W2010878661","https://openalex.org/W3147379364","https://openalex.org/W2026258298","https://openalex.org/W3204639664","https://openalex.org/W2970836791","https://openalex.org/W2805039731","https://openalex.org/W2989699735","https://openalex.org/W4322761281"],"abstract_inverted_index":{"Vision-based":[0],"hand":[1],"gesture":[2,113,141,162],"recognition":[3,114,142],"in":[4,11,42,78,115,154,193],"human-computer":[5],"interface":[6],"design":[7],"has":[8],"useful":[9],"applications":[10,26],"virtual-reality,":[12],"gaming":[13],"control,":[14],"communication":[15],"through":[16],"sign":[17],"language,":[18],"medical":[19],"rehabilitation":[20],"etc.":[21],"In":[22,95],"many":[23],"scenarios,":[24],"such":[25],"are":[27],"deployed":[28],"on":[29],"small":[30],"handheld":[31],"or":[32],"wearable":[33],"devices,":[34],"i.e.":[35],"edge":[36,194],"devices.":[37],"To":[38,164],"mitigate":[39],"the":[40,60],"challenges":[41],"building":[43],"a":[44,79,100,116,151,155,184],"real-time":[45],"convolutional":[46],"neural":[47],"network":[48,80,93,130],"(CNN)":[49],"based":[50,106],"solution":[51],"at":[52],"edge,":[53],"researchers":[54],"explore":[55],"various":[56],"methods":[57],"to":[58,138],"reduce":[59,165],"computational":[61],"overhead":[62],"during":[63],"inference.":[64],"One":[65],"recent":[66],"development":[67],"is":[68],"binarization":[69],"of":[70,187],"CNNs":[71],"that":[72,148,173],"replaces":[73],"floating":[74],"point":[75],"MAC":[76],"operations":[77],"with":[81,183,190],"efficient":[82],"XNOR-bit":[83],"count":[84],"operations,":[85,131],"thus":[86],"drastically":[87],"reducing":[88],"inference":[89,110,135,177,181],"latency,":[90],"memory":[91],"and":[92,132],"computations.":[94],"this":[96,166],"paper,":[97],"we":[98,168],"propose":[99,169],"Binary":[101],"Convolutional":[102],"Neural":[103],"Network":[104],"(BCNN)":[105],"Deep":[107],"Learning":[108],"(DL)":[109],"pipeline":[111,122],"for":[112,160],"car":[117],"infotainment":[118],"system.":[119],"Our":[120],"DL":[121],"requires":[123],"3.6x":[124],"less":[125,129,176],"storage":[126],"space,":[127],"2.3x":[128],"gives":[133],"3x":[134],"speed-up":[136,182],"compared":[137,189],"state-of-the-art":[139],"MediaPipe":[140],"system":[143],"by":[144],"Google.":[145],"We":[146],"observe":[147],"directly":[149],"binarizing":[150],"CNN":[152,192],"results":[153],"large":[156],"accuracy":[157,185],"drop":[158,186],"(48%)":[159],"our":[161],"data.":[163],"gap,":[167],"an":[170],"optimized":[171],"BCNN":[172],"uses":[174],"20x":[175],"memory,":[178],"provides":[179],"6.7x":[180],"12%":[188],"full-precision":[191],"device.":[195]},"counts_by_year":[],"updated_date":"2026-08-04T08:18:43.703281","created_date":"2025-10-10T00:00:00"}
