{"id":"https://openalex.org/W4406860668","doi":"https://doi.org/10.1109/vcip63160.2024.10849902","title":"Lightweight Graph Convolutional Network Based on Multi-Head Residual Attention for Hand Point Classification","display_name":"Lightweight Graph Convolutional Network Based on Multi-Head Residual Attention for Hand Point Classification","publication_year":2024,"publication_date":"2024-12-08","ids":{"openalex":"https://openalex.org/W4406860668","doi":"https://doi.org/10.1109/vcip63160.2024.10849902"},"language":"en","primary_location":{"id":"doi:10.1109/vcip63160.2024.10849902","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vcip63160.2024.10849902","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Visual Communications and Image Processing (VCIP)","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/A5101499271","display_name":"Duc-Chinh Nguyen","orcid":"https://orcid.org/0009-0005-3501-7018"},"institutions":[{"id":"https://openalex.org/I177233841","display_name":"Vietnam National University, Hanoi","ror":"https://ror.org/02jmfj006","country_code":"VN","type":"education","lineage":["https://openalex.org/I177233841"]}],"countries":["VN"],"is_corresponding":true,"raw_author_name":"Duc-Chinh Nguyen","raw_affiliation_strings":["Vietnam National University,Faculty of Applied Sciences International School,Hanoi,Vietnam,100000"],"affiliations":[{"raw_affiliation_string":"Vietnam National University,Faculty of Applied Sciences International School,Hanoi,Vietnam,100000","institution_ids":["https://openalex.org/I177233841"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019938778","display_name":"Manh-Hung Ha","orcid":"https://orcid.org/0000-0002-5782-6829"},"institutions":[{"id":"https://openalex.org/I177233841","display_name":"Vietnam National University, Hanoi","ror":"https://ror.org/02jmfj006","country_code":"VN","type":"education","lineage":["https://openalex.org/I177233841"]}],"countries":["VN"],"is_corresponding":false,"raw_author_name":"Manh-Hung Ha","raw_affiliation_strings":["Vietnam National University,Faculty of Applied Sciences International School,Hanoi,Vietnam,100000"],"affiliations":[{"raw_affiliation_string":"Vietnam National University,Faculty of Applied Sciences International School,Hanoi,Vietnam,100000","institution_ids":["https://openalex.org/I177233841"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062306952","display_name":"M.A. Do","orcid":"https://orcid.org/0009-0003-9300-865X"},"institutions":[{"id":"https://openalex.org/I177233841","display_name":"Vietnam National University, Hanoi","ror":"https://ror.org/02jmfj006","country_code":"VN","type":"education","lineage":["https://openalex.org/I177233841"]}],"countries":["VN"],"is_corresponding":false,"raw_author_name":"Manh-Tuan Do","raw_affiliation_strings":["Vietnam National University,Faculty of Applied Sciences International School,Hanoi,Vietnam,100000"],"affiliations":[{"raw_affiliation_string":"Vietnam National University,Faculty of Applied Sciences International School,Hanoi,Vietnam,100000","institution_ids":["https://openalex.org/I177233841"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5089896362","display_name":"Oscal Tzyh-Chiang Chen","orcid":"https://orcid.org/0000-0002-5172-9913"},"institutions":[{"id":"https://openalex.org/I163753206","display_name":"Chungbuk National University","ror":"https://ror.org/02wnxgj78","country_code":"KR","type":"education","lineage":["https://openalex.org/I163753206"]},{"id":"https://openalex.org/I148099254","display_name":"National Chung Cheng University","ror":"https://ror.org/0028v3876","country_code":"TW","type":"education","lineage":["https://openalex.org/I148099254"]}],"countries":["KR","TW"],"is_corresponding":false,"raw_author_name":"Oscal Tzyh-Chiang Chen","raw_affiliation_strings":["National ChungCheng University,Department of Electrical Engineering"],"affiliations":[{"raw_affiliation_string":"National ChungCheng University,Department of Electrical Engineering","institution_ids":["https://openalex.org/I163753206","https://openalex.org/I148099254"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5101499271"],"corresponding_institution_ids":["https://openalex.org/I177233841"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.27036373,"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":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11398","display_name":"Hand Gesture Recognition Systems","score":0.9955999851226807,"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":0.9955999851226807,"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/T14510","display_name":"Medical Imaging and Analysis","score":0.991599977016449,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.989300012588501,"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":0.7637550830841064},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.6755840182304382},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5412378907203674},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4906727075576782},{"id":"https://openalex.org/keywords/head","display_name":"Head (geology)","score":0.4676235318183899},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4460389316082001},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3463573455810547},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.2282104194164276},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.21413496136665344},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.06501182913780212}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7637550830841064},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.6755840182304382},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5412378907203674},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4906727075576782},{"id":"https://openalex.org/C2780312720","wikidata":"https://www.wikidata.org/wiki/Q5689100","display_name":"Head (geology)","level":2,"score":0.4676235318183899},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4460389316082001},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3463573455810547},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2282104194164276},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.21413496136665344},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.06501182913780212},{"id":"https://openalex.org/C114793014","wikidata":"https://www.wikidata.org/wiki/Q52109","display_name":"Geomorphology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/vcip63160.2024.10849902","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vcip63160.2024.10849902","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Visual Communications and Image Processing (VCIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W2194775991","https://openalex.org/W2886970679","https://openalex.org/W2963017945","https://openalex.org/W2963312728","https://openalex.org/W3001540518","https://openalex.org/W3101983239","https://openalex.org/W3139022918","https://openalex.org/W3158971340","https://openalex.org/W3197181216","https://openalex.org/W4205679927","https://openalex.org/W4281710609","https://openalex.org/W4292830055","https://openalex.org/W4293514615","https://openalex.org/W6720006811","https://openalex.org/W6726873649","https://openalex.org/W6745537798","https://openalex.org/W6773827925"],"related_works":["https://openalex.org/W2560215812","https://openalex.org/W2949601986","https://openalex.org/W2788972299","https://openalex.org/W2521347458","https://openalex.org/W4391621807","https://openalex.org/W2498789492","https://openalex.org/W2729981612","https://openalex.org/W4233449973","https://openalex.org/W2990636717","https://openalex.org/W4300237897"],"abstract_inverted_index":{"In":[0],"this":[1],"work,":[2],"we":[3,59],"propose":[4],"a":[5,61,75,89],"lightweight":[6],"Graph":[7],"Convolution":[8],"Network":[9],"(GCN)":[10],"based":[11],"on":[12,68,105,119,153,161,174],"residual":[13],"attention":[14,80],"model":[15,113,148],"successfully":[16],"applied":[17],"to":[18,43,82,92,171],"the":[19,34,39,44,48,52,56,69,106,111,121,133,146,154],"classification":[20],"task":[21],"of":[22,29,65],"hand":[23],"point":[24,37],"landmarks.":[25],"The":[26,102],"main":[27],"highlights":[28],"our":[30],"study":[31],"involve":[32],"redefining":[33],"standard":[35],"reference":[36],"from":[38],"initial":[40],"outer-coordinate":[41],"origin":[42],"central":[45],"position":[46],"within":[47,55,96],"palm":[49],"and":[50,123,128,164],"improving":[51],"node":[53],"features":[54],"graph.":[57],"Additionally,":[58],"construct":[60],"graph":[62,84],"network":[63],"capable":[64],"classifying":[66],"points":[67],"hand.":[70],"This":[71],"is":[72],"achieved":[73],"through":[74],"2-layer":[76],"structure,":[77],"which":[78],"incorporates":[79],"modules":[81],"optimize":[83],"information":[85],"processing,":[86],"along":[87],"with":[88],"skip":[90],"connection":[91],"prevent":[93],"feature":[94],"uniformity":[95],"nodes":[97],"after":[98],"numerous":[99],"hidden":[100],"layers.":[101],"experimental":[103],"results":[104],"ALS":[107],"dataset":[108],"indicate":[109],"that":[110],"proposed":[112,147],"yields":[114],"remarkably":[115],"high":[116,150],"accuracy":[117,151,163],"rates":[118,152],"both":[120,162],"training":[122],"test":[124],"sets,":[125],"reaching":[126],"97.75%":[127],"97.41%,":[129],"respectively,":[130],"while":[131],"keeping":[132],"computational":[134],"complexity":[135],"(parameters":[136],"are":[137],"only":[138],"25,874)":[139],"at":[140],"an":[141],"extremely":[142],"low":[143],"level.":[144],"Moreover,":[145],"exhibited":[149],"Sign":[155],"Language":[156],"MNIST":[157],"dataset,":[158],"achieving":[159],"99.41%":[160],"F1-score.":[165],"Thus,":[166],"it":[167],"has":[168],"great":[169],"potential":[170],"be":[172],"deployed":[173],"portable":[175],"devices.":[176]},"counts_by_year":[],"updated_date":"2025-12-27T23:08:20.325037","created_date":"2025-10-10T00:00:00"}
