{"id":"https://openalex.org/W4229457836","doi":"https://doi.org/10.1186/s42492-022-00111-6","title":"Analytical study of two feature extraction methods in comparison with deep learning methods for classification of small metal objects","display_name":"Analytical study of two feature extraction methods in comparison with deep learning methods for classification of small metal objects","publication_year":2022,"publication_date":"2022-05-10","ids":{"openalex":"https://openalex.org/W4229457836","doi":"https://doi.org/10.1186/s42492-022-00111-6","pmid":"https://pubmed.ncbi.nlm.nih.gov/35534747"},"language":"en","primary_location":{"id":"doi:10.1186/s42492-022-00111-6","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s42492-022-00111-6","pdf_url":"https://vciba.springeropen.com/track/pdf/10.1186/s42492-022-00111-6","source":{"id":"https://openalex.org/S3035464634","display_name":"Visual Computing for Industry Biomedicine and Art","issn_l":"2096-496X","issn":["2096-496X","2524-4442"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Visual Computing for Industry, Biomedicine, and Art","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://vciba.springeropen.com/track/pdf/10.1186/s42492-022-00111-6","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5022665785","display_name":"Somaieh Amraee","orcid":"https://orcid.org/0000-0002-1877-5774"},"institutions":[{"id":"https://openalex.org/I3131332631","display_name":"Jundi-Shapur University of Technology","ror":"https://ror.org/019f08v97","country_code":"IR","type":"education","lineage":["https://openalex.org/I3131332631"]}],"countries":["IR"],"is_corresponding":true,"raw_author_name":"Somaieh Amraee","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Jundi-Shapur University of Technology, Dezful, 64615/334, Iran. s.amraee@jsu.ac.ir","Department of Electrical and Computer Engineering, Jundi-Shapur University of Technology, Dezful, 64615/334, Iran"],"raw_orcid":"https://orcid.org/0000-0002-1877-5774","affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Jundi-Shapur University of Technology, Dezful, 64615/334, Iran. s.amraee@jsu.ac.ir","institution_ids":["https://openalex.org/I3131332631"]},{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Jundi-Shapur University of Technology, Dezful, 64615/334, Iran","institution_ids":["https://openalex.org/I3131332631"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009914203","display_name":"Maryam Chinipardaz","orcid":"https://orcid.org/0000-0001-9795-7818"},"institutions":[{"id":"https://openalex.org/I3131332631","display_name":"Jundi-Shapur University of Technology","ror":"https://ror.org/019f08v97","country_code":"IR","type":"education","lineage":["https://openalex.org/I3131332631"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Maryam Chinipardaz","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Jundi-Shapur University of Technology, Dezful, 64615/334, Iran"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Jundi-Shapur University of Technology, Dezful, 64615/334, Iran","institution_ids":["https://openalex.org/I3131332631"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5061363092","display_name":"Mohammadali Charoosaei","orcid":"https://orcid.org/0000-0001-7318-9172"},"institutions":[{"id":"https://openalex.org/I3131332631","display_name":"Jundi-Shapur University of Technology","ror":"https://ror.org/019f08v97","country_code":"IR","type":"education","lineage":["https://openalex.org/I3131332631"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Mohammadali Charoosaei","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Jundi-Shapur University of Technology, Dezful, 64615/334, Iran"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Jundi-Shapur University of Technology, Dezful, 64615/334, Iran","institution_ids":["https://openalex.org/I3131332631"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5022665785"],"corresponding_institution_ids":["https://openalex.org/I3131332631"],"apc_list":null,"apc_paid":null,"fwci":1.6258,"has_fulltext":true,"cited_by_count":16,"citation_normalized_percentile":{"value":0.84549004,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"5","issue":"1","first_page":"13","last_page":"13"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T14319","display_name":"Currency Recognition and Detection","score":0.9997000098228455,"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/T14319","display_name":"Currency Recognition and Detection","score":0.9997000098228455,"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/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9937999844551086,"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/T11212","display_name":"Cultural Heritage Materials Analysis","score":0.9717000126838684,"subfield":{"id":"https://openalex.org/subfields/1204","display_name":"Archeology"},"field":{"id":"https://openalex.org/fields/12","display_name":"Arts and Humanities"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.7812268137931824},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7783751487731934},{"id":"https://openalex.org/keywords/local-binary-patterns","display_name":"Local binary patterns","score":0.7648298740386963},{"id":"https://openalex.org/keywords/confusion-matrix","display_name":"Confusion matrix","score":0.7139649391174316},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.6277395486831665},{"id":"https://openalex.org/keywords/histogram-of-oriented-gradients","display_name":"Histogram of oriented gradients","score":0.6228460669517517},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5989004373550415},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.583450436592102},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5779297351837158},{"id":"https://openalex.org/keywords/histogram","display_name":"Histogram","score":0.5299329161643982},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4610077738761902},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.43123143911361694},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.41683095693588257}],"concepts":[{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7812268137931824},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7783751487731934},{"id":"https://openalex.org/C87335442","wikidata":"https://www.wikidata.org/wiki/Q2494345","display_name":"Local binary patterns","level":4,"score":0.7648298740386963},{"id":"https://openalex.org/C138602881","wikidata":"https://www.wikidata.org/wiki/Q2709591","display_name":"Confusion matrix","level":2,"score":0.7139649391174316},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.6277395486831665},{"id":"https://openalex.org/C17426736","wikidata":"https://www.wikidata.org/wiki/Q419918","display_name":"Histogram of oriented gradients","level":4,"score":0.6228460669517517},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5989004373550415},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.583450436592102},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5779297351837158},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.5299329161643982},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4610077738761902},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.43123143911361694},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.41683095693588257},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1186/s42492-022-00111-6","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s42492-022-00111-6","pdf_url":"https://vciba.springeropen.com/track/pdf/10.1186/s42492-022-00111-6","source":{"id":"https://openalex.org/S3035464634","display_name":"Visual Computing for Industry Biomedicine and Art","issn_l":"2096-496X","issn":["2096-496X","2524-4442"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Visual Computing for Industry, Biomedicine, and Art","raw_type":"journal-article"},{"id":"pmid:35534747","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/35534747","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":"Visual computing for industry, biomedicine, and art","raw_type":null},{"id":"pmh:oai:doaj.org/article:93967e5d2d9446f9a2f01c5d1aabde4c","is_oa":false,"landing_page_url":"https://doaj.org/article/93967e5d2d9446f9a2f01c5d1aabde4c","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Visual Computing for Industry, Biomedicine, and Art, Vol 5, Iss 1, Pp 1-13 (2022)","raw_type":"article"},{"id":"pmh:oai:pubmedcentral.nih.gov:9085991","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/9085991","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":"Vis Comput Ind Biomed Art","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.1186/s42492-022-00111-6","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s42492-022-00111-6","pdf_url":"https://vciba.springeropen.com/track/pdf/10.1186/s42492-022-00111-6","source":{"id":"https://openalex.org/S3035464634","display_name":"Visual Computing for Industry Biomedicine and Art","issn_l":"2096-496X","issn":["2096-496X","2524-4442"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Visual Computing for Industry, Biomedicine, and Art","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4229457836.pdf","grobid_xml":"https://content.openalex.org/works/W4229457836.grobid-xml"},"referenced_works_count":32,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1164457500","https://openalex.org/W1985258161","https://openalex.org/W2011349553","https://openalex.org/W2098554822","https://openalex.org/W2102605133","https://openalex.org/W2128543433","https://openalex.org/W2134475486","https://openalex.org/W2161969291","https://openalex.org/W2163352848","https://openalex.org/W2163808566","https://openalex.org/W2405334833","https://openalex.org/W2471704359","https://openalex.org/W2537323210","https://openalex.org/W2899252373","https://openalex.org/W2903824448","https://openalex.org/W2943027572","https://openalex.org/W2953536431","https://openalex.org/W2963037989","https://openalex.org/W2990171020","https://openalex.org/W3014738121","https://openalex.org/W3035967575","https://openalex.org/W3038203882","https://openalex.org/W3046891004","https://openalex.org/W3137101227","https://openalex.org/W3184246247","https://openalex.org/W3198427877","https://openalex.org/W3203198074","https://openalex.org/W3206316397","https://openalex.org/W3215807065","https://openalex.org/W3216674935","https://openalex.org/W4205717359"],"related_works":["https://openalex.org/W2181817726","https://openalex.org/W2990472155","https://openalex.org/W1566030314","https://openalex.org/W3016067690","https://openalex.org/W2769824387","https://openalex.org/W2560749169","https://openalex.org/W1974672153","https://openalex.org/W2550539038","https://openalex.org/W2750350980","https://openalex.org/W4385636057"],"abstract_inverted_index":{"This":[0],"paper":[1,130],"addresses":[2],"the":[3,21,36,45,67,78,82,85,106,144,147,153,156,162],"efficiency":[4],"of":[5,23,47,84,98,146,155,161],"two":[6,100],"feature":[7,49],"extraction":[8],"methods":[9,55,101],"for":[10,35,92],"classifying":[11],"small":[12],"metal":[13],"objects":[14],"including":[15],"screws,":[16],"nuts,":[17],"keys,":[18],"and":[19,27,42,63,87,111,136,164],"coins:":[20],"histogram":[22],"oriented":[24],"gradients":[25],"(HOG)":[26],"local":[28],"binary":[29],"pattern":[30],"(LBP).":[31],"The":[32,96,124,140],"desired":[33],"features":[34],"labeled":[37,133],"images":[38,68,135],"are":[39,69,90,119],"first":[40],"extracted":[41],"saved":[43],"in":[44,128],"form":[46],"a":[48,159],"matrix.":[50],"Using":[51],"three":[52],"different":[53,73],"classification":[54],"(non-parametric":[56],"K-nearest":[57],"neighbors":[58],"algorithm,":[59],"support":[60],"vector":[61],"machine,":[62],"na\u00efve":[64],"Bayesian":[65],"method),":[66],"classified":[70],"into":[71],"four":[72,94],"classes.":[74,95],"Then,":[75],"by":[76],"examining":[77],"resulting":[79],"confusion":[80],"matrix,":[81],"performances":[83],"HOG":[86,148,163],"LBP":[88,165],"approaches":[89],"compared":[91,104],"these":[93,99],"effectiveness":[97],"is":[102,149],"also":[103],"with":[105],"\"You":[107],"Only":[108],"Look":[109],"Once\"":[110],"faster":[112],"region-based":[113],"convolutional":[114],"neural":[115],"network":[116],"approaches,":[117],"which":[118],"based":[120],"on":[121],"deep":[122],"learning.":[123],"collected":[125],"image":[126],"set":[127],"this":[129],"includes":[131],"800":[132],"training":[134],"180":[137],"test":[138],"images.":[139],"results":[141,168],"show":[142],"that":[143],"use":[145,154],"more":[150],"efficient":[151],"than":[152,169],"LBP.":[157],"Moreover,":[158],"combination":[160],"provides":[166],"better":[167],"either":[170],"alone.":[171]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":6}],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2025-10-10T00:00:00"}