{"id":"https://openalex.org/W4391094721","doi":"https://doi.org/10.1109/icecet58911.2023.10389385","title":"Wavelet-Based RGB Hand Gesture Recognition Architecture Using Transfer Learning, a Proof-of-Concept","display_name":"Wavelet-Based RGB Hand Gesture Recognition Architecture Using Transfer Learning, a Proof-of-Concept","publication_year":2023,"publication_date":"2023-11-16","ids":{"openalex":"https://openalex.org/W4391094721","doi":"https://doi.org/10.1109/icecet58911.2023.10389385"},"language":"en","primary_location":{"id":"doi:10.1109/icecet58911.2023.10389385","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icecet58911.2023.10389385","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 International Conference on Electrical, Computer and Energy Technologies (ICECET)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5100583185","display_name":"Jose-Luis Cabra L\u00f3pez","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jose-Luis Cabra L\u00f3pez","raw_affiliation_strings":["Fundación Universitaria Compensar,Telecommunications Eng. Department,Bogotá,Colombia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fundación Universitaria Compensar,Telecommunications Eng. Department,Bogotá,Colombia","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5093760453","display_name":"Pablo Ospina","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pablo Ospina","raw_affiliation_strings":["Fundación Universitaria Compensar,Telecommunications Eng. Department,Bogotá,Colombia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fundación Universitaria Compensar,Telecommunications Eng. Department,Bogotá,Colombia","institution_ids":[]}]},{"author_position":"middle","author":{"id":null,"display_name":"Carlos Gonzalez","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Carlos Gonzalez","raw_affiliation_strings":["Fundación Universitaria Compensar,Telecommunications Eng. Department,Bogotá,Colombia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fundación Universitaria Compensar,Telecommunications Eng. Department,Bogotá,Colombia","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5093760454","display_name":"Daniel Tique","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Daniel Tique","raw_affiliation_strings":["Fundación Universitaria Compensar,Telecommunications Eng. Department,Bogotá,Colombia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fundación Universitaria Compensar,Telecommunications Eng. Department,Bogotá,Colombia","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5104232357","display_name":"Julen Rubio","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Julen Rubio","raw_affiliation_strings":["Fundación Universitaria Compensar,Software Eng. Department,Bogotá,Colombia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fundación Universitaria Compensar,Software Eng. Department,Bogotá,Colombia","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5089481644","display_name":"Leidy Hern\u00e1ndez Mesa","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Leidy Mesa","raw_affiliation_strings":["Fundación Universitaria Compensar,Software Eng. Department,Bogotá,Colombia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fundación Universitaria Compensar,Software Eng. Department,Bogotá,Colombia","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"14","issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11398","display_name":"Hand Gesture Recognition Systems","score":0.9998999834060669,"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":0.9998999834060669,"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/T10784","display_name":"Muscle activation and electromyography studies","score":0.9959999918937683,"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"}},{"id":"https://openalex.org/T11707","display_name":"Gaze Tracking and Assistive Technology","score":0.9922000169754028,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/gesture","display_name":"Gesture","score":0.8608298897743225},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7855347394943237},{"id":"https://openalex.org/keywords/gesture-recognition","display_name":"Gesture recognition","score":0.7242505550384521},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6652297973632812},{"id":"https://openalex.org/keywords/accelerometer","display_name":"Accelerometer","score":0.6318221688270569},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6058573722839355},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.592503547668457},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.5725283622741699},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4409271776676178}],"concepts":[{"id":"https://openalex.org/C207347870","wikidata":"https://www.wikidata.org/wiki/Q371174","display_name":"Gesture","level":2,"score":0.8608298897743225},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7855347394943237},{"id":"https://openalex.org/C159437735","wikidata":"https://www.wikidata.org/wiki/Q1519524","display_name":"Gesture recognition","level":3,"score":0.7242505550384521},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6652297973632812},{"id":"https://openalex.org/C89805583","wikidata":"https://www.wikidata.org/wiki/Q192940","display_name":"Accelerometer","level":2,"score":0.6318221688270569},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6058573722839355},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.592503547668457},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.5725283622741699},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4409271776676178},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icecet58911.2023.10389385","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icecet58911.2023.10389385","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 International Conference on Electrical, Computer and Energy Technologies (ICECET)","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/W168558832","https://openalex.org/W340073498","https://openalex.org/W2156762151","https://openalex.org/W2439773847","https://openalex.org/W2973104987","https://openalex.org/W2979505384","https://openalex.org/W2983683246","https://openalex.org/W3007924652","https://openalex.org/W3013154471","https://openalex.org/W3014941347","https://openalex.org/W3039938743","https://openalex.org/W3049396537","https://openalex.org/W3087079623","https://openalex.org/W3162053712","https://openalex.org/W3176939804","https://openalex.org/W3186358482","https://openalex.org/W3211023887","https://openalex.org/W3216101537","https://openalex.org/W4226251756","https://openalex.org/W4283693880","https://openalex.org/W4313065539","https://openalex.org/W4360764834","https://openalex.org/W4381569634","https://openalex.org/W4386977384"],"related_works":["https://openalex.org/W2765080098","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"],"abstract_inverted_index":{"Hand":[0],"gesture":[1,30,76,199],"recognition":[2],"is":[3],"an":[4],"area":[5],"of":[6,93,114,129,149],"human-computer":[7],"interaction":[8],"that":[9,136,163,169],"helps":[10],"to":[11,16,61,67,103,175,193],"recognize":[12],"accustomed":[13],"hand":[14,29,56,75],"gestures":[15,57,125,165],"establish":[17],"a":[18,52,74,79,127,146],"communication":[19],"interface":[20],"between":[21],"people":[22,122],"and":[23,27,44,58,97,106,151],"computers.":[24],"sEMG-,":[25],"camera-,":[26],"impedance-based":[28],"solutions":[31],"are":[32,51],"robust":[33],"orientations":[34],"but":[35],"contain":[36],"drawbacks":[37],"such":[38],"as":[39,47],"user":[40,167],"comfort,":[41],"light":[42],"sensitivity,":[43],"easy":[45],"installation,":[46],"appropriate.":[48],"Accelerometer":[49],"data":[50,192],"complementary":[53],"focus":[54],"for":[55,197],"require":[59],"only":[60],"be":[62],"positioned":[63],"over":[64],"the":[65,94,111,115,137],"object":[66],"provide":[68],"positional":[69],"information.":[70],"This":[71],"paper":[72],"performs":[73],"classification":[77,139],"with":[78,126,142,155,189],"deep":[80],"convolutional":[81],"neural":[82],"network":[83],"from":[84],"time-frequency":[85],"domain":[86],"transformed":[87],"RGB":[88,112,186],"(Red,":[89],"Green,":[90],"Blue)":[91],"images":[92],"X,":[95],"Y,":[96],"Z":[98],"accelerometer":[99,116,191],"signals.":[100,117],"We":[101,133],"propose":[102,183],"compare":[104],"GoogLeNet":[105],"ResNet":[107],"pre-trained":[108],"networks":[109],"using":[110],"approach":[113],"Our":[118],"database":[119],"included":[120],"22":[121],"containing":[123],"6":[124],"record":[128],"2000":[130],"samples":[131],"acquired.":[132],"have":[134,161],"found":[135],"best":[138],"rate":[140],"was":[141],"GoogLeNet,":[143],"which":[144],"reached":[145],"general":[147],"accuracy":[148],"91.9%":[150],"more":[152],"than":[153],"96%":[154],"some":[156],"specific":[157],"gestures.":[158],"Furthermore,":[159],"we":[160,182],"evidenced":[162],"knock-knock":[164],"possess":[166],"singularities":[168],"do":[170],"not":[171],"allow":[172],"our":[173,185],"classifier":[174],"generalize":[176],"its":[177,195],"recognition.":[178,200],"For":[179],"future":[180],"work,":[181],"testing":[184],"wavelet":[187],"architecture":[188],"smartwatch":[190],"test":[194],"capacity":[196],"wrist":[198]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2026-07-21T08:15:58.654021","created_date":"2025-10-10T00:00:00"}