{"id":"https://openalex.org/W3090097202","doi":"https://doi.org/10.1142/s021821302030001x","title":"A Two Consequent Multi-layers Deep Discriminative Approach for Classifying fMRI Images","display_name":"A Two Consequent Multi-layers Deep Discriminative Approach for Classifying fMRI Images","publication_year":2020,"publication_date":"2020-09-01","ids":{"openalex":"https://openalex.org/W3090097202","doi":"https://doi.org/10.1142/s021821302030001x","mag":"3090097202"},"language":"en","primary_location":{"id":"doi:10.1142/s021821302030001x","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s021821302030001x","pdf_url":null,"source":{"id":"https://openalex.org/S178780388","display_name":"International Journal of Artificial Intelligence Tools","issn_l":"0218-2130","issn":["0218-2130","1793-6349"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal on Artificial Intelligence Tools","raw_type":"journal-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/A5001478861","display_name":"Abeer M. Mahmoud","orcid":"https://orcid.org/0000-0002-0362-0059"},"institutions":[{"id":"https://openalex.org/I107720978","display_name":"Ain Shams University","ror":"https://ror.org/00cb9w016","country_code":"EG","type":"education","lineage":["https://openalex.org/I107720978"]}],"countries":["EG"],"is_corresponding":false,"raw_author_name":"Abeer M. Mahmoud","raw_affiliation_strings":["Computer Sciences Department, Faculty of Computer and Information Sciences, Ain Shams University, Cairo, Egypt"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Sciences Department, Faculty of Computer and Information Sciences, Ain Shams University, Cairo, Egypt","institution_ids":["https://openalex.org/I107720978"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057488732","display_name":"Hanen Karamti","orcid":"https://orcid.org/0000-0001-5162-2692"},"institutions":[{"id":"https://openalex.org/I106778892","display_name":"Princess Nourah bint Abdulrahman University","ror":"https://ror.org/05b0cyh02","country_code":"SA","type":"education","lineage":["https://openalex.org/I106778892"]},{"id":"https://openalex.org/I142899784","display_name":"University of Sfax","ror":"https://ror.org/04d4sd432","country_code":"TN","type":"education","lineage":["https://openalex.org/I142899784"]}],"countries":["SA","TN"],"is_corresponding":true,"raw_author_name":"Hanen Karamti","raw_affiliation_strings":["Computer Sciences Department, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, P. O. Box 84428, Riyadh, Saudi Arabia","MIRACL Laboratory, ISIMS, University of Sfax, B. P. 242, 3021 Sakiet Ezzit, Sfax, Tunisia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Sciences Department, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, P. O. Box 84428, Riyadh, Saudi Arabia","institution_ids":["https://openalex.org/I106778892"]},{"raw_affiliation_string":"MIRACL Laboratory, ISIMS, University of Sfax, B. P. 242, 3021 Sakiet Ezzit, Sfax, Tunisia","institution_ids":["https://openalex.org/I142899784"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5063985986","display_name":"Fadwa Alrowais","orcid":"https://orcid.org/0000-0002-8447-198X"},"institutions":[{"id":"https://openalex.org/I106778892","display_name":"Princess Nourah bint Abdulrahman University","ror":"https://ror.org/05b0cyh02","country_code":"SA","type":"education","lineage":["https://openalex.org/I106778892"]}],"countries":["SA"],"is_corresponding":false,"raw_author_name":"Fadwa Alrowais","raw_affiliation_strings":["Computer Sciences Department, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, P. O. Box 84428, Riyadh, Saudi Arabia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Sciences Department, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, P. O. Box 84428, Riyadh, Saudi Arabia","institution_ids":["https://openalex.org/I106778892"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5057488732"],"corresponding_institution_ids":["https://openalex.org/I106778892","https://openalex.org/I142899784"],"apc_list":null,"apc_paid":null,"fwci":0.3303,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.55492855,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"29","issue":"06","first_page":"2030001","last_page":"2030001"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10241","display_name":"Functional Brain Connectivity Studies","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T10241","display_name":"Functional Brain Connectivity Studies","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T12702","display_name":"Brain Tumor Detection and Classification","score":0.998199999332428,"subfield":{"id":"https://openalex.org/subfields/2808","display_name":"Neurology"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10378","display_name":"Advanced MRI Techniques and Applications","score":0.9980999827384949,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"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/computer-science","display_name":"Computer science","score":0.8786184787750244},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.8760669231414795},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.8229546546936035},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7387231588363647},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6581652164459229},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6296104788780212},{"id":"https://openalex.org/keywords/functional-magnetic-resonance-imaging","display_name":"Functional magnetic resonance imaging","score":0.6097797155380249},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.47185561060905457},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.46992695331573486},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.44322219491004944}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8786184787750244},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.8760669231414795},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8229546546936035},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7387231588363647},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6581652164459229},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6296104788780212},{"id":"https://openalex.org/C2779226451","wikidata":"https://www.wikidata.org/wiki/Q903809","display_name":"Functional magnetic resonance imaging","level":2,"score":0.6097797155380249},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.47185561060905457},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.46992695331573486},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.44322219491004944},{"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},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1142/s021821302030001x","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s021821302030001x","pdf_url":null,"source":{"id":"https://openalex.org/S178780388","display_name":"International Journal of Artificial Intelligence Tools","issn_l":"0218-2130","issn":["0218-2130","1793-6349"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal on Artificial Intelligence Tools","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.7400000095367432}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W1518405882","https://openalex.org/W1715858500","https://openalex.org/W1991933335","https://openalex.org/W2006591500","https://openalex.org/W2016709551","https://openalex.org/W2042273466","https://openalex.org/W2057607467","https://openalex.org/W2075210662","https://openalex.org/W2076063813","https://openalex.org/W2111783629","https://openalex.org/W2137746168","https://openalex.org/W2157106546","https://openalex.org/W2167868121","https://openalex.org/W2310177520","https://openalex.org/W2325276834","https://openalex.org/W2460529817","https://openalex.org/W2499800833","https://openalex.org/W2522924024","https://openalex.org/W2569531558","https://openalex.org/W2593177590","https://openalex.org/W2748583777","https://openalex.org/W2749978186","https://openalex.org/W2752558629","https://openalex.org/W2769792344","https://openalex.org/W2779020697","https://openalex.org/W2803731655","https://openalex.org/W2806873051","https://openalex.org/W2808128744","https://openalex.org/W4234063125"],"related_works":["https://openalex.org/W2159052453","https://openalex.org/W3013693939","https://openalex.org/W2669956259","https://openalex.org/W4249005693","https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W3193565141","https://openalex.org/W3133861977","https://openalex.org/W3167935049","https://openalex.org/W3029198973"],"abstract_inverted_index":{"Functional":[0],"Magnetic":[1],"Resonance":[2],"Imaging":[3],"(fMRI),":[4],"for":[5,14,49,87,123,154],"many":[6],"decades":[7],"acts":[8],"as":[9],"a":[10,114,177,202],"potential":[11],"aiding":[12],"method":[13],"diagnosing":[15],"medical":[16],"problems.":[17],"Several":[18],"successful":[19],"machine":[20],"learning":[21,50,144],"algorithms":[22,37],"have":[23],"been":[24],"proposed":[25,191],"in":[26],"literature":[27],"to":[28,63,106,146,185],"extract":[29],"valuable":[30],"knowledge":[31],"from":[32,98],"fMRI.":[33,54],"One":[34],"of":[35,53,74,83,138,150,157],"these":[36],"is":[38,56,127,132,136,176],"the":[39,58,75,81,85,88,92,99,108,151,173],"convolutional":[40],"neural":[41],"network":[42],"(CNN)":[43],"that":[44,135,180],"competent":[45],"with":[46,102,159],"high":[47],"capabilities":[48],"optimal":[51,104],"abstractions":[52],"This":[55],"because":[57],"CNN":[59,86],"learns":[60],"features":[61,105,153],"similarly":[62],"human":[64],"brain":[65,204],"where":[66],"it":[67],"preserves":[68],"local":[69],"structure":[70],"and":[71,90,165,196],"avoids":[72],"distortion":[73],"global":[76],"feature":[77],"space.":[78],"Focusing":[79],"on":[80,143,182,201],"achievements":[82],"using":[84],"fMRI,":[89],"accordingly,":[91],"Deep":[93],"Convolutional":[94],"Auto-Encoder":[95],"(DCAE)":[96],"benefits":[97],"data-driven":[100],"approach":[101,122,192],"CNN\u2019s":[103],"strengthen":[107],"fMRI":[109,125,158,206],"classification.":[110],"In":[111],"this":[112],"paper,":[113],"new":[115],"two":[116],"consequent":[117],"multi-layers":[118],"DCAE":[119,131,175],"deep":[120,169],"discriminative":[121,148],"classifying":[124],"Images":[126],"proposed.":[128],"The":[129,190],"first":[130],"unsupervised":[133],"sub-model":[134,179],"composed":[137],"four":[139],"CNN.":[140],"It":[141],"focuses":[142,181],"weights":[145],"utilize":[147],"characteristics":[149],"extracted":[152],"robust":[155],"reconstruction":[156],"lower":[160],"dimensional":[161],"considering":[162],"tiny":[163],"details":[164],"refining":[166],"by":[167],"its":[168,194],"multiple":[170],"layers.":[171],"Then":[172],"second":[174],"supervised":[178],"training":[183],"labels":[184],"reach":[186],"an":[187],"outperformed":[188],"results.":[189],"proved":[193],"effectiveness":[195],"improved":[197],"literately":[198],"reported":[199],"results":[200],"large":[203],"disorder":[205],"dataset.":[207]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}