{"id":"https://openalex.org/W2046974789","doi":"https://doi.org/10.1109/iccsce.2013.6719968","title":"A computational model of the infant pain impressions with Gaussian and Nearest Mean Classifier","display_name":"A computational model of the infant pain impressions with Gaussian and Nearest Mean Classifier","publication_year":2013,"publication_date":"2013-11-01","ids":{"openalex":"https://openalex.org/W2046974789","doi":"https://doi.org/10.1109/iccsce.2013.6719968","mag":"2046974789"},"language":"en","primary_location":{"id":"doi:10.1109/iccsce.2013.6719968","doi":"https://doi.org/10.1109/iccsce.2013.6719968","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccsce.2013.6719968","pdf_url":null,"source":{"id":"https://openalex.org/S4306418667","display_name":"IEEE International Conference on Control System, Computing and Engineering","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE International Conference on Control System, Computing and Engineering","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"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/A5055143497","display_name":"Muhammad Naufal Mansor","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I65079550","display_name":"Universiti Malaysia Perlis","ror":"https://ror.org/00xmkb790","country_code":"MY","type":"education","lineage":["https://openalex.org/I65079550"]}],"countries":["MY"],"is_corresponding":false,"raw_author_name":"Muhammad Naufal Mansor","raw_affiliation_strings":["School of Mehatronic Engineering, Universiti Malaysia Perlis, Perlis, Malaysia","Sch. of Mehatronic Eng., Univ. Malaysia Perlis, Arau, Malaysia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mehatronic Engineering, Universiti Malaysia Perlis, Perlis, Malaysia","institution_ids":["https://openalex.org/I65079550"]},{"raw_affiliation_string":"Sch. of Mehatronic Eng., Univ. Malaysia Perlis, Arau, Malaysia","institution_ids":["https://openalex.org/I65079550"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5061753581","display_name":"Muhammad Nazri Rejab","orcid":"https://orcid.org/0000-0002-9650-0784","observed_orcids":["https://orcid.org/0000-0002-9650-0784"]},"institutions":[{"id":"https://openalex.org/I4210130047","display_name":"Politeknik Tuanku Syed Sirajuddin","ror":"https://ror.org/03rj87919","country_code":"MY","type":"education","lineage":["https://openalex.org/I4210130047"]},{"id":"https://openalex.org/I65079550","display_name":"Universiti Malaysia Perlis","ror":"https://ror.org/00xmkb790","country_code":"MY","type":"education","lineage":["https://openalex.org/I65079550"]}],"countries":["MY"],"is_corresponding":false,"raw_author_name":"Mohd Nazri Rejab","raw_affiliation_strings":["School of Mehatronic Engineering, Universiti Malaysia Perlis, Perlis, Malaysia","Dept. of Mech., Politek. Tuanku Syed Sirajuddin, Arau, Malaysia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mehatronic Engineering, Universiti Malaysia Perlis, Perlis, Malaysia","institution_ids":["https://openalex.org/I65079550"]},{"raw_affiliation_string":"Dept. of Mech., Politek. Tuanku Syed Sirajuddin, Arau, Malaysia","institution_ids":["https://openalex.org/I4210130047"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":16,"citation_normalized_percentile":{"value":0.15678758,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":88,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"249","last_page":"253"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.7333999872207642,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.7333999872207642,"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/T10057","display_name":"Face and Expression Recognition","score":0.06880000233650208,"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/T11292","display_name":"Pediatric Pain Management Techniques","score":0.06369999796152115,"subfield":{"id":"https://openalex.org/subfields/2735","display_name":"Pediatrics, Perinatology and Child Health"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/facial-expression-analysis","display_name":"facial expression analysis","score":0.8820000290870667},{"id":"https://openalex.org/keywords/local-binary-pattern","display_name":"local binary pattern","score":0.8539999723434448},{"id":"https://openalex.org/keywords/feature-vectors","display_name":"feature vectors","score":0.5040000081062317},{"id":"https://openalex.org/keywords/gaussian-classifier","display_name":"Gaussian classifier","score":0.6869999766349792},{"id":"https://openalex.org/keywords/nearest-mean-classifier","display_name":"nearest mean classifier","score":0.9909999966621399},{"id":"https://openalex.org/keywords/multi-scale-retinex","display_name":"multi-scale Retinex","score":0.7979999780654907},{"id":"https://openalex.org/keywords/shadow-removal","display_name":"shadow removal","score":0.9660000205039978}],"concepts":[{"id":"https://openalex.org/C87335442","wikidata":"https://www.wikidata.org/wiki/Q2494345","display_name":"Local binary patterns","level":4,"score":0.8135308027267456},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7395493388175964},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7292531728744507},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6616026759147644},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6258466243743896},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.6038255095481873},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5264521241188049},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.4889451265335083},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.4590870141983032},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.44836071133613586},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.43389010429382324},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.16573190689086914},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iccsce.2013.6719968","doi":"https://doi.org/10.1109/iccsce.2013.6719968","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccsce.2013.6719968","pdf_url":null,"source":{"id":"https://openalex.org/S4306418667","display_name":"IEEE International Conference on Control System, Computing and Engineering","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE International Conference on Control System, Computing and Engineering","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being","score":0.8048999905586243}],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W124408761","https://openalex.org/W1482526072","https://openalex.org/W1533162639","https://openalex.org/W1554258465","https://openalex.org/W1703444797","https://openalex.org/W1978011637","https://openalex.org/W1989803413","https://openalex.org/W2017422474","https://openalex.org/W2035161948","https://openalex.org/W2039051707","https://openalex.org/W2048973207","https://openalex.org/W2049073164","https://openalex.org/W2049730379","https://openalex.org/W2066642295","https://openalex.org/W2084134149","https://openalex.org/W2096044434","https://openalex.org/W2108374065","https://openalex.org/W2108375645","https://openalex.org/W2121900453","https://openalex.org/W2128776923","https://openalex.org/W2134393319","https://openalex.org/W2143771573","https://openalex.org/W2148548654","https://openalex.org/W2150721269","https://openalex.org/W2150862990","https://openalex.org/W2169239671","https://openalex.org/W2285774314","https://openalex.org/W3017143921","https://openalex.org/W6679297202"],"related_works":["https://openalex.org/W2032241677","https://openalex.org/W4285146797","https://openalex.org/W7100808327","https://openalex.org/W1994004843","https://openalex.org/W2036896231","https://openalex.org/W2776542863","https://openalex.org/W2044542172","https://openalex.org/W2033508870","https://openalex.org/W2534646511","https://openalex.org/W2133585315"],"abstract_inverted_index":{"In":[0,57],"the":[1,39,54,76,93,101],"last":[2],"recent":[3],"years,":[4],"non-invasive":[5],"methods":[6],"through":[7],"image":[8],"analysis":[9],"of":[10,23,53,109],"facial":[11],"have":[12],"been":[13],"proved":[14],"to":[15,21,50,74],"be":[16],"excellent":[17],"and":[18,45,85],"reliable":[19],"tool":[20],"diagnose":[22],"pain":[24,40],"recognition.":[25],"This":[26],"paper":[27],"proposes":[28],"a":[29],"new":[30],"feature":[31],"vector":[32],"based":[33],"Local":[34],"Binary":[35],"Pattern":[36],"(LBP)":[37],"for":[38,91,111],"detection.":[41],"Different":[42],"sampling":[43],"point":[44],"radius":[46],"weighted":[47],"are":[48,89],"proposed":[49,55,94,102],"distinguishing":[51],"performance":[52],"features.":[56,95],"this":[58],"work,":[59],"Infant":[60,112],"COPE":[61,113],"database":[62],"is":[63,72],"used":[64],"with":[65],"illumination":[66],"added.":[67],"Multi":[68],"Scale":[69],"Retinex":[70],"(MSR)":[71],"applied":[73],"remove":[75],"shadow.":[77],"Two":[78],"different":[79],"supervised":[80],"classifiers":[81],"such":[82],"as":[83],"Gaussian":[84],"Nearest":[86],"Mean":[87],"Classifier":[88],"employed":[90],"testing":[92],"The":[96],"experimental":[97],"results":[98],"uncover":[99],"that":[100],"features":[103],"give":[104],"very":[105],"promising":[106],"classification":[107],"accuracy":[108],"90%":[110],"database.":[114]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":6},{"year":2017,"cited_by_count":2}],"updated_date":"2026-10-16T09:59:22.235173","created_date":"2016-06-24T00:00:00"}
