{"id":"https://openalex.org/W3127627067","doi":"https://doi.org/10.1109/access.2021.3055826","title":"A Convolutional Neural Network Approach to the Classification of Engineering Models","display_name":"A Convolutional Neural Network Approach to the Classification of Engineering Models","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W3127627067","doi":"https://doi.org/10.1109/access.2021.3055826","mag":"3127627067"},"language":"en","primary_location":{"id":"doi:10.1109/access.2021.3055826","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3055826","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09343314.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"public-domain","license_id":"https://openalex.org/licenses/public-domain","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09343314.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5052771319","display_name":"Bharadwaj Manda","orcid":"https://orcid.org/0000-0001-7282-4525"},"institutions":[{"id":"https://openalex.org/I24676775","display_name":"Indian Institute of Technology Madras","ror":"https://ror.org/03v0r5n49","country_code":"IN","type":"facility","lineage":["https://openalex.org/I24676775"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Bharadwaj Manda","raw_affiliation_strings":["Advanced Geometric Computing Laboratory, Indian Institute of Technology Madras, Chennai, India"],"raw_orcid":"https://orcid.org/0000-0001-7282-4525","affiliations":[{"raw_affiliation_string":"Advanced Geometric Computing Laboratory, Indian Institute of Technology Madras, Chennai, India","institution_ids":["https://openalex.org/I24676775"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062447052","display_name":"Pranjal Bhaskare","orcid":"https://orcid.org/0000-0002-3846-9758"},"institutions":[{"id":"https://openalex.org/I24676775","display_name":"Indian Institute of Technology Madras","ror":"https://ror.org/03v0r5n49","country_code":"IN","type":"facility","lineage":["https://openalex.org/I24676775"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Pranjal Bhaskare","raw_affiliation_strings":["Advanced Geometric Computing Laboratory, Indian Institute of Technology Madras, Chennai, India"],"raw_orcid":"https://orcid.org/0000-0002-3846-9758","affiliations":[{"raw_affiliation_string":"Advanced Geometric Computing Laboratory, Indian Institute of Technology Madras, Chennai, India","institution_ids":["https://openalex.org/I24676775"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5078092370","display_name":"Ramanathan Muthuganapathy","orcid":"https://orcid.org/0000-0003-0182-977X"},"institutions":[{"id":"https://openalex.org/I24676775","display_name":"Indian Institute of Technology Madras","ror":"https://ror.org/03v0r5n49","country_code":"IN","type":"facility","lineage":["https://openalex.org/I24676775"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Ramanathan Muthuganapathy","raw_affiliation_strings":["Advanced Geometric Computing Laboratory, Indian Institute of Technology Madras, Chennai, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Advanced Geometric Computing Laboratory, Indian Institute of Technology Madras, Chennai, India","institution_ids":["https://openalex.org/I24676775"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5052771319"],"corresponding_institution_ids":["https://openalex.org/I24676775"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":4.2312,"has_fulltext":true,"cited_by_count":37,"citation_normalized_percentile":{"value":0.94423204,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"9","issue":null,"first_page":"22711","last_page":"22723"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11159","display_name":"Manufacturing Process and Optimization","score":0.9961000084877014,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"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/T11159","display_name":"Manufacturing Process and Optimization","score":0.9961000084877014,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing 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/T14339","display_name":"Image Processing and 3D Reconstruction","score":0.988099992275238,"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/T13113","display_name":"Engineering Technology and Methodologies","score":0.9714000225067139,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing 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":0.754879891872406},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.635284960269928},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4497263431549072},{"id":"https://openalex.org/keywords/neural-engineering","display_name":"Neural engineering","score":0.43034231662750244},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4238245487213135},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3287120461463928}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.754879891872406},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.635284960269928},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4497263431549072},{"id":"https://openalex.org/C168451700","wikidata":"https://www.wikidata.org/wiki/Q1306528","display_name":"Neural engineering","level":2,"score":0.43034231662750244},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4238245487213135},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3287120461463928}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/access.2021.3055826","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3055826","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09343314.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"public-domain","license_id":"https://openalex.org/licenses/public-domain","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:2107.06481","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2107.06481","pdf_url":"https://arxiv.org/pdf/2107.06481","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":null,"raw_type":"text"},{"id":"pmh:oai:doaj.org/article:c34a59b582b9422587da1d269f92299a","is_oa":true,"landing_page_url":"https://doaj.org/article/c34a59b582b9422587da1d269f92299a","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":"IEEE Access, Vol 9, Pp 22711-22723 (2021)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2021.3055826","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3055826","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09343314.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"public-domain","license_id":"https://openalex.org/licenses/public-domain","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","score":0.5899999737739563,"id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320309036","display_name":"Purdue University","ror":"https://ror.org/02dqehb95"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3127627067.pdf","grobid_xml":"https://content.openalex.org/works/W3127627067.grobid-xml"},"referenced_works_count":70,"referenced_works":["https://openalex.org/W1498436455","https://openalex.org/W1522301498","https://openalex.org/W1644641054","https://openalex.org/W1686810756","https://openalex.org/W1806891645","https://openalex.org/W1920022804","https://openalex.org/W1972893558","https://openalex.org/W1984020445","https://openalex.org/W2006013468","https://openalex.org/W2021122545","https://openalex.org/W2027148423","https://openalex.org/W2034216041","https://openalex.org/W2042096371","https://openalex.org/W2046150577","https://openalex.org/W2073840674","https://openalex.org/W2080067164","https://openalex.org/W2091365875","https://openalex.org/W2095705004","https://openalex.org/W2097117768","https://openalex.org/W2099789128","https://openalex.org/W2101234009","https://openalex.org/W2106404777","https://openalex.org/W2115182825","https://openalex.org/W2117539524","https://openalex.org/W2124561101","https://openalex.org/W2140833774","https://openalex.org/W2151587352","https://openalex.org/W2162251358","https://openalex.org/W2163605009","https://openalex.org/W2170194874","https://openalex.org/W2194775991","https://openalex.org/W2211722331","https://openalex.org/W2295332248","https://openalex.org/W2295598076","https://openalex.org/W2402144811","https://openalex.org/W2474603704","https://openalex.org/W2523246573","https://openalex.org/W2555254696","https://openalex.org/W2560609797","https://openalex.org/W2566979684","https://openalex.org/W2578436806","https://openalex.org/W2592242041","https://openalex.org/W2788151339","https://openalex.org/W2797161036","https://openalex.org/W2898227265","https://openalex.org/W2942231644","https://openalex.org/W2952689920","https://openalex.org/W2953384591","https://openalex.org/W2962731536","https://openalex.org/W2962835968","https://openalex.org/W2963121255","https://openalex.org/W2964121744","https://openalex.org/W2972931660","https://openalex.org/W3102476541","https://openalex.org/W3125937743","https://openalex.org/W3129544473","https://openalex.org/W6631190155","https://openalex.org/W6637373629","https://openalex.org/W6638520917","https://openalex.org/W6640300118","https://openalex.org/W6674330103","https://openalex.org/W6674914833","https://openalex.org/W6675354045","https://openalex.org/W6680887930","https://openalex.org/W6684191040","https://openalex.org/W6713134421","https://openalex.org/W6727249380","https://openalex.org/W6732286402","https://openalex.org/W6739778489","https://openalex.org/W6755712434"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W4387369504","https://openalex.org/W3046775127","https://openalex.org/W4394896187","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W3107602296","https://openalex.org/W4364306694","https://openalex.org/W4312192474"],"abstract_inverted_index":{"This":[0],"paper":[1],"presents":[2],"a":[3,99,104,113,161],"deep":[4,38,178],"learning":[5],"approach":[6,192],"for":[7,41,65,75,117],"the":[8,21,33,51,66,121,134,140,148,156,187,194,203],"classification":[9,43,70,205],"of":[10,23,35,47,53,68,71,136,152],"Engineering":[11,84],"(CAD)":[12],"models":[13,79,96],"using":[14,98,160,177,193],"Convolutional":[15],"Neural":[16],"Networks":[17],"(CNNs).":[18],"Owing":[19],"to":[20,102,111,147],"availability":[22],"large":[24],"annotated":[25],"datasets":[26],"and":[27,55,92,139],"also":[28],"enough":[29],"computational":[30],"power":[31],"in":[32,50,155],"form":[34,103],"GPUs,":[36],"many":[37],"learning-based":[39],"solutions":[40,61],"object":[42],"have":[44,62,80,166],"been":[45,63,81,167],"proposed":[46,64,110,195],"late,":[48],"especially":[49],"domain":[52],"images":[54,142],"graphical":[56],"models.":[57,73],"Nevertheless,":[58],"very":[59],"few":[60],"task":[67],"functional":[69],"CAD":[72,78],"Hence,":[74],"this":[76],"research,":[77],"collected":[82],"from":[83],"Shape":[85],"Benchmark":[86],"(ESB),":[87],"National":[88],"Design":[89],"Repository":[90],"(NDR)":[91],"augmented":[93],"with":[94,169,199],"newer":[95],"created":[97],"modeling":[100],"software":[101],"dataset":[105,157],"-":[106],"`CADNET'.":[107],"It":[108],"is":[109,131,158],"use":[112],"residual":[114],"network":[115,184,196],"architecture":[116],"CADNET,":[118],"inspired":[119],"by":[120],"popular":[122],"ResNet.":[123],"A":[124],"weighted":[125],"Light":[126],"Field":[127],"Descriptor":[128],"(LFD)":[129],"scheme":[130],"chosen":[132],"as":[133,145,173,180,182],"method":[135],"feature":[137],"extraction,":[138],"generated":[141],"are":[143],"fed":[144],"inputs":[146],"CNN.":[149],"The":[150,189],"problem":[151],"class":[153,162],"imbalance":[154],"addressed":[159],"weights":[163],"approach.":[164],"Experiments":[165],"conducted":[168],"other":[170,183],"signatures":[171],"such":[172],"geodesic":[174],"distance":[175],"etc.":[176],"networks":[179],"well":[181],"architectures":[185],"on":[186,207],"CADNET.":[188,208],"LFD-based":[190],"CNN":[191],"architecture,":[197],"along":[198],"gradient":[200],"boosting":[201],"yielded":[202],"best":[204],"accuracy":[206]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":13},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":2}],"updated_date":"2026-05-29T09:21:14.243279","created_date":"2021-02-15T00:00:00"}
