{"id":"https://openalex.org/W4391366483","doi":"https://doi.org/10.51865/jpgt.2023.02.17","title":"COMPARATIVE ANALYSIS OF OBJECT CLASSIFICATION ALGORITHMS: TRADITIONAL IMAGE PROCESSING VERSUS ARTIFICIAL INTELLIGENCE \u2013 BASED APPROACH","display_name":"COMPARATIVE ANALYSIS OF OBJECT CLASSIFICATION ALGORITHMS: TRADITIONAL IMAGE PROCESSING VERSUS ARTIFICIAL INTELLIGENCE \u2013 BASED APPROACH","publication_year":2023,"publication_date":"2023-12-30","ids":{"openalex":"https://openalex.org/W4391366483","doi":"https://doi.org/10.51865/jpgt.2023.02.17"},"language":"en","primary_location":{"id":"doi:10.51865/jpgt.2023.02.17","doi":"https://doi.org/10.51865/jpgt.2023.02.17","is_oa":true,"landing_page_url":"https://doi.org/10.51865/jpgt.2023.02.17","pdf_url":"https://doi.org/10.51865/jpgt.2023.02.17","source":{"id":"https://openalex.org/S4210233524","display_name":"Romanian Journal of Petroleum & Gas Technology","issn_l":"2734-5319","issn":["2734-5319","2972-0370"],"is_oa":true,"is_in_doaj":true,"is_core":false,"listed_in":["doaj"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Romanian Journal of Petroleum &amp; Gas Technology","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://doi.org/10.51865/jpgt.2023.02.17","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5074509233","display_name":"Cosmina-Mihaela Ro\u0219ca","orcid":"https://orcid.org/0000-0003-0827-3321","observed_orcids":["https://orcid.org/0000-0003-0827-3321"]},"institutions":[{"id":"https://openalex.org/I4210090220","display_name":"Petroleum & Gas University of Ploie\u015fti","ror":"https://ror.org/00abdnc40","country_code":"RO","type":"education","lineage":["https://openalex.org/I4210090220"]}],"countries":["RO"],"is_corresponding":true,"raw_author_name":"Cosmina Mihaela Rosca","raw_affiliation_strings":["Petroleum-Gas University of Ploie\u0219ti , Romania"],"raw_orcid":"https://orcid.org/0000-0003-0827-3321","affiliations":[{"raw_affiliation_string":"Petroleum-Gas University of Ploie\u0219ti , Romania","institution_ids":["https://openalex.org/I4210090220"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5074509233"],"corresponding_institution_ids":["https://openalex.org/I4210090220"],"apc_list":null,"apc_paid":null,"fwci":1.7132,"has_fulltext":true,"cited_by_count":23,"citation_normalized_percentile":{"value":0.85756161,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":93,"max":100},"biblio":{"volume":"4 (75)","issue":"2","first_page":"169","last_page":"180"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10601","display_name":"Handwritten Text Recognition Techniques","score":0.9984999895095825,"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"}},"topics":[{"id":"https://openalex.org/T10601","display_name":"Handwritten Text Recognition Techniques","score":0.9984999895095825,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.00039999998989515007,"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/T13674","display_name":"Computer Science and Engineering","score":0.0003000000142492354,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/shape-recognition","display_name":"shape recognition","score":0.9729999899864197},{"id":"https://openalex.org/keywords/object-classification","display_name":"object classification","score":0.9409999847412109},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"artificial intelligence","score":0.6359999775886536},{"id":"https://openalex.org/keywords/image-processing","display_name":"image processing","score":0.8209999799728394},{"id":"https://openalex.org/keywords/neural-network","display_name":"artificial neural networks","score":0.9120000004768372},{"id":"https://openalex.org/keywords/edge-detection","display_name":"edge detection","score":0.9919999837875366},{"id":"https://openalex.org/keywords/contour-analysis","display_name":"contour analysis","score":1.0},{"id":"https://openalex.org/keywords/recognition-accuracy","display_name":"recognition accuracy","score":0.3779999911785126}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7668100595474243},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.655550479888916},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6308194994926453},{"id":"https://openalex.org/C104317675","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Digital image processing","level":4,"score":0.5590958595275879},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5036613345146179},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.5003793239593506},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.480380117893219},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3951897919178009},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.28927403688430786},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2757143974304199}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.51865/jpgt.2023.02.17","doi":"https://doi.org/10.51865/jpgt.2023.02.17","is_oa":true,"landing_page_url":"https://doi.org/10.51865/jpgt.2023.02.17","pdf_url":"https://doi.org/10.51865/jpgt.2023.02.17","source":{"id":"https://openalex.org/S4210233524","display_name":"Romanian Journal of Petroleum & Gas Technology","issn_l":"2734-5319","issn":["2734-5319","2972-0370"],"is_oa":true,"is_in_doaj":true,"is_core":false,"listed_in":["doaj"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Romanian Journal of Petroleum &amp; Gas Technology","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:9e9cc98e5e1149e1821dbc5fddb55ca0","doi":null,"is_oa":true,"landing_page_url":"https://doaj.org/article/9e9cc98e5e1149e1821dbc5fddb55ca0","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,"listed_in":[],"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":"Romanian Journal of Petroleum & Gas Technology, Vol 4, Iss 2, Pp 169-180 (2023)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.51865/jpgt.2023.02.17","doi":"https://doi.org/10.51865/jpgt.2023.02.17","is_oa":true,"landing_page_url":"https://doi.org/10.51865/jpgt.2023.02.17","pdf_url":"https://doi.org/10.51865/jpgt.2023.02.17","source":{"id":"https://openalex.org/S4210233524","display_name":"Romanian Journal of Petroleum & Gas Technology","issn_l":"2734-5319","issn":["2734-5319","2972-0370"],"is_oa":true,"is_in_doaj":true,"is_core":false,"listed_in":["doaj"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Romanian Journal of Petroleum &amp; Gas Technology","raw_type":"journal-article"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4391366483.pdf","grobid_xml":"https://content.openalex.org/works/W4391366483.grobid-xml"},"referenced_works_count":15,"referenced_works":["https://openalex.org/W180219488","https://openalex.org/W2162789522","https://openalex.org/W2489523345","https://openalex.org/W2501120992","https://openalex.org/W2890671392","https://openalex.org/W2901758161","https://openalex.org/W2962845546","https://openalex.org/W3022366539","https://openalex.org/W3036355034","https://openalex.org/W3117263089","https://openalex.org/W3134203554","https://openalex.org/W4224920452","https://openalex.org/W4252200669","https://openalex.org/W4285205078","https://openalex.org/W4361855169"],"related_works":["https://openalex.org/W4415970079","https://openalex.org/W7120030836","https://openalex.org/W2016162824","https://openalex.org/W2004577461","https://openalex.org/W4411023184","https://openalex.org/W4404624082","https://openalex.org/W2393371403","https://openalex.org/W4407163995","https://openalex.org/W3114598677","https://openalex.org/W2366137339"],"abstract_inverted_index":{"In":[0],"the":[1,36,51,55,97,119,131,136,158],"current":[2],"era":[3],"of":[4,28,38,99,130,138,148,160,203],"advanced":[5],"digital":[6],"technologies,":[7],"form":[8,31,62,73,124,140,172],"recognition":[9,32,74,125,141,173],"is":[10,48,104,133,155],"integrated":[11],"into":[12],"numerous":[13],"applications,":[14],"from":[15],"computer":[16],"vision":[17],"to":[18,53,93,105,121,134,156,164],"industrial":[19],"automation.":[20],"This":[21,87],"paper":[22,132],"focuses":[23],"on":[24,67,181,188,199],"a":[25,65,112,185,200],"comparative":[26],"analysis":[27,214],"two":[29],"distinct":[30],"algorithms,":[33],"namely":[34],"harnessing":[35],"power":[37],"artificial":[39,182],"intelligence":[40,183],"(AI)":[41],"and":[42,59,83,96,115,150,177,184,212],"image":[43,71,143,189,206],"processing":[44,207],"techniques.":[45,215],"The":[46,102,127,152,191,205],"research":[47],"motivated":[49],"by":[50],"need":[52],"address":[54],"trade-off":[56],"between":[57],"speed":[58,149],"complexity":[60,88],"in":[61,146],"recognition,":[63],"with":[64,142],"center":[66],"real-world":[68],"applicability.":[69],"Traditional":[70],"processing-based":[72,144],"approaches":[75],"often":[76],"require":[77],"complex":[78],"coding,":[79],"substantial":[80],"domain":[81],"expertise,":[82],"significant":[84],"computational":[85],"resources.":[86],"can":[89,110],"hinder":[90],"rapid":[91],"adaptation":[92],"changing":[94],"requirements":[95],"addition":[98],"new":[100,165],"forms.":[101,204],"aim":[103],"explore":[106],"whether":[107],"AI-powered":[108,192],"algorithms":[109,163,174],"offer":[111],"more":[113],"efficient":[114],"versatile":[116],"alternative,":[117],"reducing":[118],"barriers":[120],"entry":[122],"for":[123],"tasks.":[126],"primary":[128],"goal":[129,154],"compare":[135],"performance":[137],"AI-based":[139,162],"methods":[145],"terms":[147],"accuracy.":[151],"second":[153,186],"assess":[157],"ease":[159],"adapting":[161],"forms":[166],"without":[167],"extensive":[168],"code":[169],"changes.":[170],"Two":[171],"were":[175],"designed":[176],"implemented,":[178],"one":[179],"based":[180],"relying":[187],"processing.":[190],"algorithm":[193,208],"uses":[194],"neural":[195],"network":[196],"architecture":[197],"trained":[198],"predefined":[201],"dataset":[202],"employs":[209],"edge":[210],"detection":[211],"contour":[213]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":19},{"year":2024,"cited_by_count":2}],"updated_date":"2026-11-05T12:25:35.769452","created_date":"2024-01-31T00:00:00"}
