{"id":"https://openalex.org/W3090587901","doi":"https://doi.org/10.1109/ijcnn48605.2020.9206886","title":"Hybrid Gray-Scale and Fuzzy Morphological/Linear Perceptrons Trained By Extreme Learning Machine","display_name":"Hybrid Gray-Scale and Fuzzy Morphological/Linear Perceptrons Trained By Extreme Learning Machine","publication_year":2020,"publication_date":"2020-07-01","ids":{"openalex":"https://openalex.org/W3090587901","doi":"https://doi.org/10.1109/ijcnn48605.2020.9206886","mag":"3090587901"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn48605.2020.9206886","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn48605.2020.9206886","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 International Joint Conference on Neural Networks (IJCNN)","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/A5078829305","display_name":"Peter Sussner","orcid":"https://orcid.org/0000-0002-8457-7127"},"institutions":[{"id":"https://openalex.org/I181391015","display_name":"Universidade Estadual de Campinas (UNICAMP)","ror":"https://ror.org/04wffgt70","country_code":"BR","type":"education","lineage":["https://openalex.org/I181391015"]}],"countries":["BR"],"is_corresponding":true,"raw_author_name":"Peter Sussner","raw_affiliation_strings":["Dept. of Applied Math, IMECC University of Campinas, Campinas, SP, Brazil"],"affiliations":[{"raw_affiliation_string":"Dept. of Applied Math, IMECC University of Campinas, Campinas, SP, Brazil","institution_ids":["https://openalex.org/I181391015"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015086663","display_name":"Israel Campiott","orcid":null},"institutions":[{"id":"https://openalex.org/I4210144446","display_name":"Brazilian Institute of Neuroscience and Neurotechnology","ror":"https://ror.org/044ydn458","country_code":"BR","type":"facility","lineage":["https://openalex.org/I4210144446"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Israel Campiott","raw_affiliation_strings":["NeuralMind, Campinas, SP, Brazil"],"affiliations":[{"raw_affiliation_string":"NeuralMind, Campinas, SP, Brazil","institution_ids":["https://openalex.org/I4210144446"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5007348705","display_name":"Manuel Alejandro Quispe Torres","orcid":"https://orcid.org/0000-0002-8036-0932"},"institutions":[{"id":"https://openalex.org/I181391015","display_name":"Universidade Estadual de Campinas (UNICAMP)","ror":"https://ror.org/04wffgt70","country_code":"BR","type":"education","lineage":["https://openalex.org/I181391015"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Manuel Alejandro Quispe Torres","raw_affiliation_strings":["Dept. of Applied Math, IMECC University of Campinas, Campinas, SP, Brazil"],"affiliations":[{"raw_affiliation_string":"Dept. of Applied Math, IMECC University of Campinas, Campinas, SP, Brazil","institution_ids":["https://openalex.org/I181391015"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5078829305"],"corresponding_institution_ids":["https://openalex.org/I181391015"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.11870501,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"13","issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12676","display_name":"Machine Learning and ELM","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T12676","display_name":"Machine Learning and ELM","score":1.0,"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"}},{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9987999796867371,"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"}},{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9909999966621399,"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/perceptron","display_name":"Perceptron","score":0.8472445011138916},{"id":"https://openalex.org/keywords/sigmoid-function","display_name":"Sigmoid function","score":0.8234467506408691},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6523841619491577},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6124391555786133},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.60898357629776},{"id":"https://openalex.org/keywords/mathematical-morphology","display_name":"Mathematical morphology","score":0.6078325510025024},{"id":"https://openalex.org/keywords/extreme-learning-machine","display_name":"Extreme learning machine","score":0.5798727869987488},{"id":"https://openalex.org/keywords/differentiable-function","display_name":"Differentiable function","score":0.558312177658081},{"id":"https://openalex.org/keywords/fuzzy-logic","display_name":"Fuzzy logic","score":0.5201571583747864},{"id":"https://openalex.org/keywords/activation-function","display_name":"Activation function","score":0.44391563534736633},{"id":"https://openalex.org/keywords/multilayer-perceptron","display_name":"Multilayer perceptron","score":0.4126480221748352},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3951747715473175},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3356410562992096},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.30872485041618347},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.09586194157600403}],"concepts":[{"id":"https://openalex.org/C60908668","wikidata":"https://www.wikidata.org/wiki/Q690207","display_name":"Perceptron","level":3,"score":0.8472445011138916},{"id":"https://openalex.org/C81388566","wikidata":"https://www.wikidata.org/wiki/Q526668","display_name":"Sigmoid function","level":3,"score":0.8234467506408691},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6523841619491577},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6124391555786133},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.60898357629776},{"id":"https://openalex.org/C185568154","wikidata":"https://www.wikidata.org/wiki/Q530242","display_name":"Mathematical morphology","level":4,"score":0.6078325510025024},{"id":"https://openalex.org/C2780150128","wikidata":"https://www.wikidata.org/wiki/Q21948731","display_name":"Extreme learning machine","level":3,"score":0.5798727869987488},{"id":"https://openalex.org/C202615002","wikidata":"https://www.wikidata.org/wiki/Q783507","display_name":"Differentiable function","level":2,"score":0.558312177658081},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.5201571583747864},{"id":"https://openalex.org/C38365724","wikidata":"https://www.wikidata.org/wiki/Q4677469","display_name":"Activation function","level":3,"score":0.44391563534736633},{"id":"https://openalex.org/C179717631","wikidata":"https://www.wikidata.org/wiki/Q2991667","display_name":"Multilayer perceptron","level":3,"score":0.4126480221748352},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3951747715473175},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3356410562992096},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.30872485041618347},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.09586194157600403},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn48605.2020.9206886","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn48605.2020.9206886","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":46,"referenced_works":["https://openalex.org/W49612063","https://openalex.org/W1013078494","https://openalex.org/W1495623034","https://openalex.org/W1504863246","https://openalex.org/W1506806321","https://openalex.org/W1540852386","https://openalex.org/W1554663460","https://openalex.org/W1590218343","https://openalex.org/W1963789760","https://openalex.org/W1963848754","https://openalex.org/W1966639131","https://openalex.org/W1987924114","https://openalex.org/W1999014607","https://openalex.org/W2018992668","https://openalex.org/W2026131661","https://openalex.org/W2031888308","https://openalex.org/W2045151223","https://openalex.org/W2047028564","https://openalex.org/W2048306705","https://openalex.org/W2097998348","https://openalex.org/W2104307771","https://openalex.org/W2104622509","https://openalex.org/W2111072639","https://openalex.org/W2117812871","https://openalex.org/W2121402967","https://openalex.org/W2122776051","https://openalex.org/W2138046150","https://openalex.org/W2153342234","https://openalex.org/W2161126623","https://openalex.org/W2301541953","https://openalex.org/W2480422823","https://openalex.org/W2613427450","https://openalex.org/W2896808092","https://openalex.org/W2913706141","https://openalex.org/W2973651390","https://openalex.org/W2982160266","https://openalex.org/W2995012499","https://openalex.org/W3023169168","https://openalex.org/W4212952892","https://openalex.org/W4236245678","https://openalex.org/W4248734160","https://openalex.org/W4250661196","https://openalex.org/W4255455317","https://openalex.org/W6674385629","https://openalex.org/W6767780160","https://openalex.org/W7066626507"],"related_works":["https://openalex.org/W3024979424","https://openalex.org/W4283785902","https://openalex.org/W3032499992","https://openalex.org/W2041004593","https://openalex.org/W3134817226","https://openalex.org/W2895192346","https://openalex.org/W3110577345","https://openalex.org/W1969847908","https://openalex.org/W2053362666","https://openalex.org/W4205825681"],"abstract_inverted_index":{"Morphological":[0],"perceptrons":[1,117],"(MPs)":[2],"belong":[3],"to":[4,68,87,103,112],"the":[5,44,51,55,63,66,79,129,132,135,138],"class":[6],"of":[7,29,54,65,75,81,131,140,147],"morphological":[8,82],"neural":[9,47],"networks":[10],"(MNNs)":[11],"whose":[12],"neuronal":[13],"aggregation":[14,34],"functions":[15,61],"are":[16],"drawn":[17],"from":[18],"mathematical":[19,31],"morphology":[20,32],"(MM).":[21],"Most":[22],"MNN":[23],"models":[24,143],"including":[25],"MPs":[26],"employ":[27],"operators":[28,109],"gray-scale":[30,98],"as":[33],"functions.":[35,71],"Recently,":[36],"a":[37,73,145],"hybrid":[38,114],"morphological/linear":[39,116],"perceptron":[40,57],"(HMLP)":[41],"appeared":[42],"in":[43,124,144],"literature.":[45],"This":[46],"network":[48],"model":[49],"combines":[50],"approximation":[52],"capabilities":[53],"two-layer":[56],"having":[58],"sigmoid":[59],"activation":[60],"with":[62,137],"capability":[64],"MP":[67],"represent":[69],"non-differentiable":[70],"For":[72],"number":[74,146],"reasons,":[76],"that":[77,97],"include":[78],"non-differentiability":[80],"operators,":[83],"it":[84],"is":[85,100],"advantageous":[86],"train":[88,120],"HMLPs":[89],"using":[90,122],"extreme":[91],"learning":[92],"machine":[93],"(ELM).":[94],"The":[95],"fact":[96],"MM":[99,105],"closely":[101],"related":[102,142],"fuzzy":[104,115],"based":[106],"on":[107],"Lukasiewicz":[108],"motivated":[110],"us":[111],"introduce":[113],"(FMLPs)":[118],"and":[119,134],"them":[121],"ELM":[123],"this":[125],"paper.":[126],"We":[127],"compare":[128],"performances":[130],"HMLP":[133],"FMLP":[136],"ones":[139],"some":[141],"well-known":[148],"classification":[149],"problems.":[150]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
