{"id":"https://openalex.org/W4296365158","doi":"https://doi.org/10.3390/s22187040","title":"Deep Neural Network for 3D Shape Classification Based on Mesh Feature","display_name":"Deep Neural Network for 3D Shape Classification Based on Mesh Feature","publication_year":2022,"publication_date":"2022-09-17","ids":{"openalex":"https://openalex.org/W4296365158","doi":"https://doi.org/10.3390/s22187040","pmid":"https://pubmed.ncbi.nlm.nih.gov/36146387"},"language":"en","primary_location":{"id":"doi:10.3390/s22187040","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s22187040","pdf_url":"https://www.mdpi.com/1424-8220/22/18/7040/pdf?version=1663404652","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1424-8220/22/18/7040/pdf?version=1663404652","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5084353352","display_name":"Mengran Gao","orcid":"https://orcid.org/0000-0002-7031-3120"},"institutions":[{"id":"https://openalex.org/I177739611","display_name":"Yangtze University","ror":"https://ror.org/05bhmhz54","country_code":"CN","type":"education","lineage":["https://openalex.org/I177739611"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mengran Gao","raw_affiliation_strings":["School of Electronic and Information, Yangtze University, Jingzhou 434023, China"],"raw_orcid":"https://orcid.org/0000-0002-7031-3120","affiliations":[{"raw_affiliation_string":"School of Electronic and Information, Yangtze University, Jingzhou 434023, China","institution_ids":["https://openalex.org/I177739611"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013004591","display_name":"Ningjun Ruan","orcid":"https://orcid.org/0000-0001-5387-1801"},"institutions":[{"id":"https://openalex.org/I177739611","display_name":"Yangtze University","ror":"https://ror.org/05bhmhz54","country_code":"CN","type":"education","lineage":["https://openalex.org/I177739611"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Ningjun Ruan","raw_affiliation_strings":["School of Electronic and Information, Yangtze University, Jingzhou 434023, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronic and Information, Yangtze University, Jingzhou 434023, China","institution_ids":["https://openalex.org/I177739611"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063149968","display_name":"Junpeng Shi","orcid":"https://orcid.org/0000-0002-9910-0663"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junpeng Shi","raw_affiliation_strings":["College of Electronic Countermeasure, National University of Defense Technology, Hefei 230037, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Electronic Countermeasure, National University of Defense Technology, Hefei 230037, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101200532","display_name":"Wanli Zhou","orcid":null},"institutions":[{"id":"https://openalex.org/I177739611","display_name":"Yangtze University","ror":"https://ror.org/05bhmhz54","country_code":"CN","type":"education","lineage":["https://openalex.org/I177739611"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wanli Zhou","raw_affiliation_strings":["School of Electronic and Information, Yangtze University, Jingzhou 434023, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronic and Information, Yangtze University, Jingzhou 434023, China","institution_ids":["https://openalex.org/I177739611"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5013004591"],"corresponding_institution_ids":["https://openalex.org/I177739611"],"apc_list":{"value":2400,"currency":"CHF","value_usd":2598},"apc_paid":{"value":2400,"currency":"CHF","value_usd":2598},"fwci":1.6604,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.81011468,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"22","issue":"18","first_page":"7040","last_page":"7040"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T10481","display_name":"Computer Graphics and Visualization Techniques","score":0.9965000152587891,"subfield":{"id":"https://openalex.org/subfields/1704","display_name":"Computer Graphics and Computer-Aided Design"},"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/T11211","display_name":"3D Surveying and Cultural Heritage","score":0.9933000206947327,"subfield":{"id":"https://openalex.org/subfields/1907","display_name":"Geology"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/polygon-mesh","display_name":"Polygon mesh","score":0.8815134763717651},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7387180328369141},{"id":"https://openalex.org/keywords/triangle-mesh","display_name":"Triangle mesh","score":0.712954044342041},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6401454210281372},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6090337634086609},{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.5559619665145874},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5250102281570435},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4724567234516144},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.46609795093536377},{"id":"https://openalex.org/keywords/mesh-generation","display_name":"Mesh generation","score":0.4561973214149475},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4467789828777313},{"id":"https://openalex.org/keywords/adjacency-matrix","display_name":"Adjacency matrix","score":0.432896226644516},{"id":"https://openalex.org/keywords/voxel","display_name":"Voxel","score":0.4303736686706543},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.42394542694091797},{"id":"https://openalex.org/keywords/adjacency-list","display_name":"Adjacency list","score":0.414419949054718},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.20933124423027039},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.1731800138950348},{"id":"https://openalex.org/keywords/computer-graphics","display_name":"Computer graphics (images)","score":0.1534343957901001},{"id":"https://openalex.org/keywords/finite-element-method","display_name":"Finite element method","score":0.089453786611557},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.081271231174469}],"concepts":[{"id":"https://openalex.org/C31487907","wikidata":"https://www.wikidata.org/wiki/Q1154597","display_name":"Polygon mesh","level":2,"score":0.8815134763717651},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7387180328369141},{"id":"https://openalex.org/C194401833","wikidata":"https://www.wikidata.org/wiki/Q3456889","display_name":"Triangle mesh","level":3,"score":0.712954044342041},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6401454210281372},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6090337634086609},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.5559619665145874},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5250102281570435},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4724567234516144},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.46609795093536377},{"id":"https://openalex.org/C181145010","wikidata":"https://www.wikidata.org/wiki/Q4418033","display_name":"Mesh generation","level":3,"score":0.4561973214149475},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4467789828777313},{"id":"https://openalex.org/C180356752","wikidata":"https://www.wikidata.org/wiki/Q727035","display_name":"Adjacency matrix","level":3,"score":0.432896226644516},{"id":"https://openalex.org/C54170458","wikidata":"https://www.wikidata.org/wiki/Q663554","display_name":"Voxel","level":2,"score":0.4303736686706543},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.42394542694091797},{"id":"https://openalex.org/C110484373","wikidata":"https://www.wikidata.org/wiki/Q264398","display_name":"Adjacency list","level":2,"score":0.414419949054718},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.20933124423027039},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.1731800138950348},{"id":"https://openalex.org/C121684516","wikidata":"https://www.wikidata.org/wiki/Q7600677","display_name":"Computer graphics (images)","level":1,"score":0.1534343957901001},{"id":"https://openalex.org/C135628077","wikidata":"https://www.wikidata.org/wiki/Q220184","display_name":"Finite element method","level":2,"score":0.089453786611557},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.081271231174469},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true}],"locations_count":5,"locations":[{"id":"doi:10.3390/s22187040","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s22187040","pdf_url":"https://www.mdpi.com/1424-8220/22/18/7040/pdf?version=1663404652","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},{"id":"pmid:36146387","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/36146387","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:doaj.org/article:243f7dfd36ce4736a07e11a3f7c47147","is_oa":true,"landing_page_url":"https://doaj.org/article/243f7dfd36ce4736a07e11a3f7c47147","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors, Vol 22, Iss 18, p 7040 (2022)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/1424-8220/22/18/7040/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/s22187040","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"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":"Sensors; Volume 22; Issue 18; Pages: 7040","raw_type":"Text"},{"id":"pmh:oai:pubmedcentral.nih.gov:9506136","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/9506136","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"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":"Sensors (Basel)","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/s22187040","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s22187040","pdf_url":"https://www.mdpi.com/1424-8220/22/18/7040/pdf?version=1663404652","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4296365158.pdf","grobid_xml":"https://content.openalex.org/works/W4296365158.grobid-xml"},"referenced_works_count":40,"referenced_works":["https://openalex.org/W1644641054","https://openalex.org/W2098350864","https://openalex.org/W2137420960","https://openalex.org/W2146527621","https://openalex.org/W2211722331","https://openalex.org/W2556802233","https://openalex.org/W2560609797","https://openalex.org/W2606202972","https://openalex.org/W2624503621","https://openalex.org/W2766448241","https://openalex.org/W2799162093","https://openalex.org/W2898797193","https://openalex.org/W2902078856","https://openalex.org/W2940374047","https://openalex.org/W2944930481","https://openalex.org/W2962731536","https://openalex.org/W2962928871","https://openalex.org/W2963053547","https://openalex.org/W2963719584","https://openalex.org/W2963727135","https://openalex.org/W2963830382","https://openalex.org/W2979750740","https://openalex.org/W2990613095","https://openalex.org/W3009238340","https://openalex.org/W3012015905","https://openalex.org/W3034681945","https://openalex.org/W3035002114","https://openalex.org/W3042388945","https://openalex.org/W3102669005","https://openalex.org/W3110800655","https://openalex.org/W3177008250","https://openalex.org/W3203718246","https://openalex.org/W4200141118","https://openalex.org/W4225320889","https://openalex.org/W4241422529","https://openalex.org/W6640300118","https://openalex.org/W6668523581","https://openalex.org/W6747904511","https://openalex.org/W6756601264","https://openalex.org/W6774105919"],"related_works":["https://openalex.org/W4213150077","https://openalex.org/W2369410163","https://openalex.org/W2059018062","https://openalex.org/W2604585036","https://openalex.org/W2078477160","https://openalex.org/W1989103179","https://openalex.org/W1991172810","https://openalex.org/W125803343","https://openalex.org/W2153421018","https://openalex.org/W2117632582"],"abstract_inverted_index":{"Virtual":[0],"reality,":[1],"driverless":[2],"cars,":[3],"and":[4,49,59,78],"robotics":[5],"all":[6],"make":[7],"extensive":[8],"use":[9],"of":[10,15,88,126],"3D":[11,22,42,70],"shape":[12,71],"classification.":[13],"One":[14],"the":[16,120,130],"most":[17],"popular":[18],"ways":[19],"to":[20,56,111],"represent":[21],"data":[23,43],"is":[24,32,55],"with":[25,123],"polygonal":[26],"meshes.":[27],"In":[28,66],"particular,":[29],"triangular":[30,36,76,86],"mesh":[31,37,64,77,102,113],"frequently":[33],"employed.":[34],"A":[35],"has":[38],"more":[39],"features":[40],"than":[41],"formats":[44],"such":[45],"as":[46,93],"voxels,":[47],"multi-views,":[48],"point":[50],"clouds.":[51],"The":[52,85,115],"current":[53],"challenge":[54],"fully":[57],"utilize":[58],"extract":[60],"useful":[61],"information":[62],"from":[63,101],"data.":[65,114],"this":[67,89,134],"paper,":[68],"a":[69,94],"classification":[72,131],"network":[73,132],"based":[74],"on":[75,119],"graph":[79,104],"convolutional":[80,105],"neural":[81,106],"networks":[82,107],"was":[83,91],"suggested.":[84],"face":[87],"model":[90],"viewed":[92],"unit.":[95],"By":[96],"obtaining":[97],"an":[98,124],"adjacency":[99],"matrix":[100],"data,":[103],"can":[108],"be":[109],"utilized":[110],"process":[112],"studies":[116],"were":[117],"performed":[118],"ModelNet40":[121],"dataset":[122],"accuracy":[125],"91.0%,":[127],"demonstrating":[128],"that":[129],"in":[133],"research":[135],"may":[136],"produce":[137],"effective":[138],"results.":[139]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2}],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2025-10-10T00:00:00"}