{"id":"https://openalex.org/W4317600351","doi":"https://doi.org/10.1109/aiccsa56895.2022.10017591","title":"Convolutional, Extra-Trees and Multi layer Perceptron","display_name":"Convolutional, Extra-Trees and Multi layer Perceptron","publication_year":2022,"publication_date":"2022-12-01","ids":{"openalex":"https://openalex.org/W4317600351","doi":"https://doi.org/10.1109/aiccsa56895.2022.10017591"},"language":"en","primary_location":{"id":"doi:10.1109/aiccsa56895.2022.10017591","is_oa":false,"landing_page_url":"https://doi.org/10.1109/aiccsa56895.2022.10017591","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE/ACS 19th International Conference on Computer Systems and Applications (AICCSA)","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/A5035622939","display_name":"Abdelkader Berrouachedi","orcid":"https://orcid.org/0000-0002-3959-9271"},"institutions":[{"id":"https://openalex.org/I48825208","display_name":"Universit\u00e9 Paris 8","ror":"https://ror.org/04wez5e68","country_code":"FR","type":"education","lineage":["https://openalex.org/I48825208"]}],"countries":["FR"],"is_corresponding":true,"raw_author_name":"Abdelkader Berrouachedi","raw_affiliation_strings":["University of Paris VIII,Paragraphe research Lab,Paris,France","Paragraphe research Lab, University of Paris VIII, Paris, France"],"affiliations":[{"raw_affiliation_string":"University of Paris VIII,Paragraphe research Lab,Paris,France","institution_ids":["https://openalex.org/I48825208"]},{"raw_affiliation_string":"Paragraphe research Lab, University of Paris VIII, Paris, France","institution_ids":["https://openalex.org/I48825208"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018166832","display_name":"Rakia Jaziri","orcid":null},"institutions":[{"id":"https://openalex.org/I48825208","display_name":"Universit\u00e9 Paris 8","ror":"https://ror.org/04wez5e68","country_code":"FR","type":"education","lineage":["https://openalex.org/I48825208"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Rakia Jaziri","raw_affiliation_strings":["University of Paris VIII,Paragraphe research Lab,Paris,France","Paragraphe research Lab, University of Paris VIII, Paris, France"],"affiliations":[{"raw_affiliation_string":"University of Paris VIII,Paragraphe research Lab,Paris,France","institution_ids":["https://openalex.org/I48825208"]},{"raw_affiliation_string":"Paragraphe research Lab, University of Paris VIII, Paris, France","institution_ids":["https://openalex.org/I48825208"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5049573335","display_name":"Gilles Bernard","orcid":null},"institutions":[{"id":"https://openalex.org/I48825208","display_name":"Universit\u00e9 Paris 8","ror":"https://ror.org/04wez5e68","country_code":"FR","type":"education","lineage":["https://openalex.org/I48825208"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Gilles Bernard","raw_affiliation_strings":["University of Paris VIII,Paragraphe research Lab,Paris,France","Paragraphe research Lab, University of Paris VIII, Paris, France"],"affiliations":[{"raw_affiliation_string":"University of Paris VIII,Paragraphe research Lab,Paris,France","institution_ids":["https://openalex.org/I48825208"]},{"raw_affiliation_string":"Paragraphe research Lab, University of Paris VIII, Paris, France","institution_ids":["https://openalex.org/I48825208"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5035622939"],"corresponding_institution_ids":["https://openalex.org/I48825208"],"apc_list":null,"apc_paid":null,"fwci":0.6631,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.74991304,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.998199999332428,"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/T10320","display_name":"Neural Networks and Applications","score":0.998199999332428,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9976999759674072,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.996399998664856,"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/computer-science","display_name":"Computer science","score":0.8303325176239014},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7456985116004944},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7117512822151184},{"id":"https://openalex.org/keywords/decision-tree","display_name":"Decision tree","score":0.6589678525924683},{"id":"https://openalex.org/keywords/initialization","display_name":"Initialization","score":0.6402719616889954},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6009403467178345},{"id":"https://openalex.org/keywords/perceptron","display_name":"Perceptron","score":0.5651196837425232},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5511007308959961},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.515012264251709},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5037238001823425},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4983654022216797},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.48972180485725403},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.48532313108444214},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.45831888914108276},{"id":"https://openalex.org/keywords/multilayer-perceptron","display_name":"Multilayer perceptron","score":0.436083048582077},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.07640597224235535}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8303325176239014},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7456985116004944},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7117512822151184},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.6589678525924683},{"id":"https://openalex.org/C114466953","wikidata":"https://www.wikidata.org/wiki/Q6034165","display_name":"Initialization","level":2,"score":0.6402719616889954},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6009403467178345},{"id":"https://openalex.org/C60908668","wikidata":"https://www.wikidata.org/wiki/Q690207","display_name":"Perceptron","level":3,"score":0.5651196837425232},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5511007308959961},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.515012264251709},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5037238001823425},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4983654022216797},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.48972180485725403},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.48532313108444214},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.45831888914108276},{"id":"https://openalex.org/C179717631","wikidata":"https://www.wikidata.org/wiki/Q2991667","display_name":"Multilayer perceptron","level":3,"score":0.436083048582077},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.07640597224235535},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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":1,"locations":[{"id":"doi:10.1109/aiccsa56895.2022.10017591","is_oa":false,"landing_page_url":"https://doi.org/10.1109/aiccsa56895.2022.10017591","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE/ACS 19th International Conference on Computer Systems and Applications (AICCSA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/15","display_name":"Life in Land","score":0.6899999976158142}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":44,"referenced_works":["https://openalex.org/W104441265","https://openalex.org/W164607750","https://openalex.org/W1538131130","https://openalex.org/W1625941627","https://openalex.org/W1852455026","https://openalex.org/W1967865200","https://openalex.org/W1990106316","https://openalex.org/W2056132907","https://openalex.org/W2064769840","https://openalex.org/W2124436456","https://openalex.org/W2146831490","https://openalex.org/W2155893237","https://openalex.org/W2191835017","https://openalex.org/W2194775991","https://openalex.org/W2220384803","https://openalex.org/W2249382963","https://openalex.org/W2282861635","https://openalex.org/W2342242867","https://openalex.org/W2560674852","https://openalex.org/W2586062600","https://openalex.org/W2587398863","https://openalex.org/W2592340788","https://openalex.org/W2611953050","https://openalex.org/W2740144340","https://openalex.org/W2772678462","https://openalex.org/W2810818231","https://openalex.org/W2890560993","https://openalex.org/W2911964244","https://openalex.org/W2919115771","https://openalex.org/W2962772482","https://openalex.org/W2963037989","https://openalex.org/W2964110616","https://openalex.org/W2964321699","https://openalex.org/W2972272278","https://openalex.org/W2992518310","https://openalex.org/W2997979403","https://openalex.org/W3018929474","https://openalex.org/W6628973269","https://openalex.org/W6632100814","https://openalex.org/W6632481002","https://openalex.org/W6684191040","https://openalex.org/W6700618171","https://openalex.org/W6720006811","https://openalex.org/W6754723338"],"related_works":["https://openalex.org/W2118162660","https://openalex.org/W1486989822","https://openalex.org/W2249059179","https://openalex.org/W4366990902","https://openalex.org/W4317732970","https://openalex.org/W4388550696","https://openalex.org/W4321636153","https://openalex.org/W4313289487","https://openalex.org/W2076543106","https://openalex.org/W2994772185"],"abstract_inverted_index":{"In":[0,112],"this":[1,113],"paper,":[2],"we":[3,115],"propose":[4],"a":[5,40,68,82,151],"novel":[6],"approach":[7,145],"for":[8,25,135,150],"building":[9,128],"and":[10,28,30,55,62,108,132,155,168],"initializing":[11],"deep":[12,44],"neural":[13,37,93,110],"networks":[14,38,94],"based":[15],"on":[16],"extremely":[17],"randomized":[18],"trees":[19,107],"(extra-trees)":[20],"an":[21],"ensemble":[22],"learning":[23,45],"method":[24,100],"both":[26],"classification":[27,156],"regression":[29,154],"feature":[31],"extraction":[32],"techniques.":[33],"We":[34],"use":[35],"convolutional":[36],"(CNNs),":[39],"family":[41],"of":[42,52,65,88,119,129,153],"modern":[43],"models,":[46],"extensively":[47],"used":[48],"in":[49],"the":[50,60,79,86,89,92,117,120,123,127,130,133,143],"area":[51],"computer":[53],"vision":[54],"image":[56],"classification,":[57],"to":[58,73,165],"improve":[59],"accuracy":[61],"generalization":[63],"performance":[64,149],"classifiers.":[66],"First,":[67],"CNN":[69],"model":[70],"is":[71],"built":[72],"automatically":[74],"extract":[75],"multi-level":[76],"features":[77],"from":[78],"data.":[80],"Second,":[81],"random":[83],"forest":[84],"obtains":[85],"structures":[87],"trees.":[90],"Finally,":[91],"(MLP)":[95],"are":[96],"built.":[97],"This":[98],"hybrid":[99,121],"combines":[101],"two":[102],"standard":[103],"adaptive":[104],"methods:":[105],"decision":[106],"artificial":[109],"networks.":[111],"article,":[114],"illustrate":[116],"structure":[118],"method,":[122],"problems":[124],"occurring":[125],"during":[126],"model,":[131],"solutions":[134],"these":[136],"problems.":[137],"The":[138],"experimental":[139],"results":[140,159],"indicate":[141],"that":[142],"proposed":[144],"achieves":[146],"consistently":[147],"high":[148],"variety":[152],"tasks.":[157],"These":[158],"should":[160],"motivate":[161],"further":[162],"studies":[163],"seeking":[164],"develop":[166],"accurate":[167],"efficient":[169],"tree-based":[170],"models.":[171]},"counts_by_year":[{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
