{"id":"https://openalex.org/W4312857950","doi":"https://doi.org/10.1109/iicaiet55139.2022.9936857","title":"Classification of Contaminants in Glass Recycling Using Hybrid CNN-SVM Model","display_name":"Classification of Contaminants in Glass Recycling Using Hybrid CNN-SVM Model","publication_year":2022,"publication_date":"2022-09-13","ids":{"openalex":"https://openalex.org/W4312857950","doi":"https://doi.org/10.1109/iicaiet55139.2022.9936857"},"language":"en","primary_location":{"id":"doi:10.1109/iicaiet55139.2022.9936857","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iicaiet55139.2022.9936857","pdf_url":null,"source":{"id":"https://openalex.org/S4363608273","display_name":"2022 IEEE International Conference on Artificial Intelligence in Engineering and Technology (IICAIET)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Conference on Artificial Intelligence in Engineering and Technology (IICAIET)","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/A5051635113","display_name":"Ho Qiu Ann Juliana","orcid":null},"institutions":[{"id":"https://openalex.org/I155043079","display_name":"University of Nottingham Malaysia Campus","ror":"https://ror.org/04mz9mt17","country_code":"MY","type":"education","lineage":["https://openalex.org/I142263535","https://openalex.org/I155043079"]}],"countries":["MY"],"is_corresponding":true,"raw_author_name":"Ho Qiu Ann Juliana","raw_affiliation_strings":["University of Nottingham Malaysia,Department of Mechanical, Materials and Manufacturing Engineering,Semenyih,Malaysia","Department of Mechanical, Materials and Manufacturing Engineering, University of Nottingham Malaysia, Semenyih, Malaysia"],"affiliations":[{"raw_affiliation_string":"University of Nottingham Malaysia,Department of Mechanical, Materials and Manufacturing Engineering,Semenyih,Malaysia","institution_ids":["https://openalex.org/I155043079"]},{"raw_affiliation_string":"Department of Mechanical, Materials and Manufacturing Engineering, University of Nottingham Malaysia, Semenyih, Malaysia","institution_ids":["https://openalex.org/I155043079"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056713915","display_name":"Novita Sakundarini","orcid":"https://orcid.org/0000-0002-7998-2910"},"institutions":[{"id":"https://openalex.org/I155043079","display_name":"University of Nottingham Malaysia Campus","ror":"https://ror.org/04mz9mt17","country_code":"MY","type":"education","lineage":["https://openalex.org/I142263535","https://openalex.org/I155043079"]}],"countries":["MY"],"is_corresponding":false,"raw_author_name":"Novita Sakundarini","raw_affiliation_strings":["University of Nottingham Malaysia,Department of Mechanical, Materials and Manufacturing Engineering,Semenyih,Malaysia","Department of Mechanical, Materials and Manufacturing Engineering, University of Nottingham Malaysia, Semenyih, Malaysia"],"affiliations":[{"raw_affiliation_string":"University of Nottingham Malaysia,Department of Mechanical, Materials and Manufacturing Engineering,Semenyih,Malaysia","institution_ids":["https://openalex.org/I155043079"]},{"raw_affiliation_string":"Department of Mechanical, Materials and Manufacturing Engineering, University of Nottingham Malaysia, Semenyih, Malaysia","institution_ids":["https://openalex.org/I155043079"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5006626905","display_name":"Lim Chin Seong","orcid":null},"institutions":[{"id":"https://openalex.org/I155043079","display_name":"University of Nottingham Malaysia Campus","ror":"https://ror.org/04mz9mt17","country_code":"MY","type":"education","lineage":["https://openalex.org/I142263535","https://openalex.org/I155043079"]}],"countries":["MY"],"is_corresponding":false,"raw_author_name":"Lim Chin Seong","raw_affiliation_strings":["University of Nottingham Malaysia,Department of Mechanical, Materials and Manufacturing Engineering,Semenyih,Malaysia","Department of Mechanical, Materials and Manufacturing Engineering, University of Nottingham Malaysia, Semenyih, Malaysia"],"affiliations":[{"raw_affiliation_string":"University of Nottingham Malaysia,Department of Mechanical, Materials and Manufacturing Engineering,Semenyih,Malaysia","institution_ids":["https://openalex.org/I155043079"]},{"raw_affiliation_string":"Department of Mechanical, Materials and Manufacturing Engineering, University of Nottingham Malaysia, Semenyih, Malaysia","institution_ids":["https://openalex.org/I155043079"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5051635113"],"corresponding_institution_ids":["https://openalex.org/I155043079"],"apc_list":null,"apc_paid":null,"fwci":0.3466,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.49897049,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9937000274658203,"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/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9937000274658203,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9822999835014343,"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/T12874","display_name":"Digital Imaging for Blood Diseases","score":0.9804999828338623,"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/support-vector-machine","display_name":"Support vector machine","score":0.8374654054641724},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7216535806655884},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6871469616889954},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6630314588546753},{"id":"https://openalex.org/keywords/extractor","display_name":"Extractor","score":0.6429328918457031},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5810027122497559},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5565398335456848},{"id":"https://openalex.org/keywords/sorting","display_name":"Sorting","score":0.4397313892841339},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.433150976896286},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3735874593257904},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.36057525873184204},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.11249813437461853},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.10998466610908508},{"id":"https://openalex.org/keywords/process-engineering","display_name":"Process engineering","score":0.06756892800331116}],"concepts":[{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.8374654054641724},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7216535806655884},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6871469616889954},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6630314588546753},{"id":"https://openalex.org/C117978034","wikidata":"https://www.wikidata.org/wiki/Q5422192","display_name":"Extractor","level":2,"score":0.6429328918457031},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5810027122497559},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5565398335456848},{"id":"https://openalex.org/C111696304","wikidata":"https://www.wikidata.org/wiki/Q2303697","display_name":"Sorting","level":2,"score":0.4397313892841339},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.433150976896286},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3735874593257904},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.36057525873184204},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.11249813437461853},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.10998466610908508},{"id":"https://openalex.org/C21880701","wikidata":"https://www.wikidata.org/wiki/Q2144042","display_name":"Process engineering","level":1,"score":0.06756892800331116}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iicaiet55139.2022.9936857","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iicaiet55139.2022.9936857","pdf_url":null,"source":{"id":"https://openalex.org/S4363608273","display_name":"2022 IEEE International Conference on Artificial Intelligence in Engineering and Technology (IICAIET)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Conference on Artificial Intelligence in Engineering and Technology (IICAIET)","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":27,"referenced_works":["https://openalex.org/W1686810756","https://openalex.org/W1950888772","https://openalex.org/W2071640528","https://openalex.org/W2097117768","https://openalex.org/W2116008226","https://openalex.org/W2137664016","https://openalex.org/W2163605009","https://openalex.org/W2230241016","https://openalex.org/W2294345429","https://openalex.org/W2559881210","https://openalex.org/W2574787443","https://openalex.org/W2605899186","https://openalex.org/W2611290057","https://openalex.org/W2801148351","https://openalex.org/W2900782514","https://openalex.org/W2911155906","https://openalex.org/W2919358988","https://openalex.org/W2951603627","https://openalex.org/W2968532074","https://openalex.org/W2980718568","https://openalex.org/W6637373629","https://openalex.org/W6674914833","https://openalex.org/W6683595889","https://openalex.org/W6684191040","https://openalex.org/W6697166373","https://openalex.org/W6737171491","https://openalex.org/W6767349813"],"related_works":["https://openalex.org/W3082848404","https://openalex.org/W1979583797","https://openalex.org/W2016864125","https://openalex.org/W2739612537","https://openalex.org/W4293226380","https://openalex.org/W3141979996","https://openalex.org/W2945706271","https://openalex.org/W4387435415","https://openalex.org/W2114169842","https://openalex.org/W2535808783"],"abstract_inverted_index":{"The":[0,61,78,115,239],"sorting":[1],"process":[2],"of":[3,12,26,83,105,117,150,157,171,179,201,223,230,235],"glass":[4,13,29,256],"recycling":[5],"is":[6,100,132,141,161,242],"crucial":[7],"to":[8,19,52,107,163,218,249],"determine":[9],"the":[10,24,54,90,110,129,153,155,158,164,169,177,197,204,208,212,221],"grade":[11,255],"cullet.":[14],"Hence,":[15],"this":[16,147,175],"paper":[17],"aims":[18],"develop":[20],"an":[21,75],"algorithm":[22],"for":[23],"classification":[25,59,172,199],"contaminants":[27,84],"in":[28,57,112,128,146,152,168],"recycling,":[30],"presenting":[31],"a":[32,103],"hybrid":[33,79,130,159],"model":[34,67,80,131,214],"integrating":[35],"two":[36],"remarkable":[37],"classifiers:":[38],"Convolutional":[39],"Neural":[40],"Network":[41],"(CNN)":[42],"and":[43,72,88,126,134,181,191,232,237,245],"Support":[44],"Vector":[45],"Machines":[46],"(SVM),":[47],"which":[48],"have":[49],"been":[50],"proven":[51],"achieve":[53],"state-of-the-art":[55],"results":[56],"solving":[58],"problem.":[60],"proposed":[62,240],"approach":[63,144],"utilizes":[64],"pre-trained":[65,120],"CNN":[66,121,166],"as":[68,74,189,247],"automatic":[69],"feature":[70,82],"extractor":[71],"SVM":[73,182,188],"output":[76],"predictor.":[77],"extracts":[81],"from":[85],"raw":[86],"images":[87,99],"predicts":[89],"corresponding":[91],"class.":[92],"A":[93],"contaminant":[94],"database":[95],"consisting":[96],"around":[97],"2000":[98],"collected":[101],"with":[102,187,193,215],"set":[104],"constraints":[106],"best":[108],"portray":[109],"realism":[111],"practical":[113],"environment.":[114],"performance":[116,156],"three":[118],"different":[119],"models":[122,160,167],"(i.e.":[123],"AlexNet,":[124],"VGG-16":[125,180],"GoogLeNet)":[127],"tested":[133],"evaluated":[135],"using":[136],"comparative":[137],"analysis.":[138],"Since":[139],"there":[140],"no":[142],"similar":[143],"used":[145],"research":[148],"field":[149],"interest":[151],"past,":[154],"compared":[162,248],"fine-tuned":[165],"aspect":[170],"accuracy.":[173],"In":[174],"study,":[176],"integration":[178],"was":[183],"improved":[184],"by":[185],"0.17%":[186],"classifier":[190],"0.50%":[192],"data":[194,216],"augmentation,":[195],"achieving":[196],"highest":[198],"accuracy":[200],"100%":[202],"among":[203],"other":[205],"models.":[206],"Among":[207],"factors":[209],"that":[210],"cause":[211],"VGG-16+SVM":[213],"augmentation":[217],"outperform":[219],"are":[220],"depth":[222],"network,":[224],"input":[225],"size,":[226,228],"stride":[227],"size":[229],"filters":[231],"total":[233],"number":[234],"weights":[236],"MACs.":[238],"method":[241],"more":[243],"accurate":[244],"efficient":[246],"current":[250],"existing":[251],"method,":[252],"producing":[253],"high":[254],"cullet":[257],"at":[258],"low":[259],"cost.":[260]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2026-03-25T13:04:00.132906","created_date":"2025-10-10T00:00:00"}