{"id":"https://openalex.org/W2736263403","doi":"https://doi.org/10.1109/ijcnn.2017.7966211","title":"Object recognition using cellular simultaneous recurrent networks and convolutional neural network","display_name":"Object recognition using cellular simultaneous recurrent networks and convolutional neural network","publication_year":2017,"publication_date":"2017-05-01","ids":{"openalex":"https://openalex.org/W2736263403","doi":"https://doi.org/10.1109/ijcnn.2017.7966211","mag":"2736263403"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2017.7966211","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2017.7966211","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 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/A5083608547","display_name":"Md Zahangir Alom","orcid":"https://orcid.org/0000-0002-2314-1207"},"institutions":[{"id":"https://openalex.org/I127591826","display_name":"University of Dayton","ror":"https://ror.org/021v3qy27","country_code":"US","type":"education","lineage":["https://openalex.org/I127591826"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Md Zahangir Alom","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Dayton, OH, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Dayton, OH, USA","institution_ids":["https://openalex.org/I127591826"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068456323","display_name":"Mahbubul Alam","orcid":"https://orcid.org/0000-0002-7159-709X"},"institutions":[{"id":"https://openalex.org/I81365321","display_name":"Old Dominion University","ror":"https://ror.org/04zjtrb98","country_code":"US","type":"education","lineage":["https://openalex.org/I81365321"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"M. Alam","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Old Dominion University, VA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Old Dominion University, VA, USA","institution_ids":["https://openalex.org/I81365321"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5104090957","display_name":"Tarek M. Taha","orcid":null},"institutions":[{"id":"https://openalex.org/I127591826","display_name":"University of Dayton","ror":"https://ror.org/021v3qy27","country_code":"US","type":"education","lineage":["https://openalex.org/I127591826"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tarek M. Taha","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Dayton, OH, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Dayton, OH, USA","institution_ids":["https://openalex.org/I127591826"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5081863591","display_name":"Khan M. Iftekharuddin","orcid":"https://orcid.org/0000-0001-8316-4163"},"institutions":[{"id":"https://openalex.org/I81365321","display_name":"Old Dominion University","ror":"https://ror.org/04zjtrb98","country_code":"US","type":"education","lineage":["https://openalex.org/I81365321"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"K. M. Iftekharuddin","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Old Dominion University, VA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Old Dominion University, VA, USA","institution_ids":["https://openalex.org/I81365321"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5083608547"],"corresponding_institution_ids":["https://openalex.org/I127591826"],"apc_list":null,"apc_paid":null,"fwci":2.3402,"has_fulltext":false,"cited_by_count":24,"citation_normalized_percentile":{"value":0.9115437,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"2873","last_page":"2880"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12676","display_name":"Machine Learning and ELM","score":0.9998000264167786,"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":0.9998000264167786,"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/T10502","display_name":"Advanced Memory and Neural Computing","score":0.9972000122070312,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T10320","display_name":"Neural Networks and Applications","score":0.9921000003814697,"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/convolutional-neural-network","display_name":"Convolutional neural network","score":0.8331279754638672},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7988952994346619},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7887910604476929},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6922959089279175},{"id":"https://openalex.org/keywords/cognitive-neuroscience-of-visual-object-recognition","display_name":"Cognitive neuroscience of visual object recognition","score":0.62388676404953},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5724980235099792},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5251742601394653},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.48473069071769714},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.45280197262763977},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4255070984363556}],"concepts":[{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.8331279754638672},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7988952994346619},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7887910604476929},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6922959089279175},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.62388676404953},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5724980235099792},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5251742601394653},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.48473069071769714},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.45280197262763977},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4255070984363556}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn.2017.7966211","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2017.7966211","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":53,"referenced_works":["https://openalex.org/W1566309885","https://openalex.org/W1620607163","https://openalex.org/W1631921255","https://openalex.org/W1665214252","https://openalex.org/W1824921430","https://openalex.org/W1841450225","https://openalex.org/W1861148776","https://openalex.org/W1904365287","https://openalex.org/W1969322166","https://openalex.org/W1973497318","https://openalex.org/W1977574351","https://openalex.org/W1993717606","https://openalex.org/W1993845689","https://openalex.org/W2026131661","https://openalex.org/W2062118960","https://openalex.org/W2085367457","https://openalex.org/W2087042989","https://openalex.org/W2091856807","https://openalex.org/W2097117768","https://openalex.org/W2098580305","https://openalex.org/W2100495367","https://openalex.org/W2102680763","https://openalex.org/W2103560185","https://openalex.org/W2105922750","https://openalex.org/W2107025852","https://openalex.org/W2108201967","https://openalex.org/W2108598243","https://openalex.org/W2111072639","https://openalex.org/W2124285714","https://openalex.org/W2124914669","https://openalex.org/W2136922672","https://openalex.org/W2140085497","https://openalex.org/W2140833774","https://openalex.org/W2144157433","https://openalex.org/W2149009003","https://openalex.org/W2154422044","https://openalex.org/W2155904486","https://openalex.org/W2156163116","https://openalex.org/W2160121923","https://openalex.org/W2163605009","https://openalex.org/W2171108400","https://openalex.org/W2541841318","https://openalex.org/W2963173190","https://openalex.org/W4231109964","https://openalex.org/W6637242042","https://openalex.org/W6638759419","https://openalex.org/W6639225255","https://openalex.org/W6648737282","https://openalex.org/W6678801095","https://openalex.org/W6680887930","https://openalex.org/W6681456260","https://openalex.org/W6684191040","https://openalex.org/W7074671674"],"related_works":["https://openalex.org/W4226493464","https://openalex.org/W3133861977","https://openalex.org/W2951211570","https://openalex.org/W3103566983","https://openalex.org/W2949096641","https://openalex.org/W2969228573","https://openalex.org/W2970686063","https://openalex.org/W4320729701","https://openalex.org/W2963690996","https://openalex.org/W4254103348"],"abstract_inverted_index":{"In":[0,56],"recent":[1],"years,":[2],"Convolutional":[3,72],"Neural":[4],"Networks":[5,63,73,91],"(CNNs)":[6],"have":[7,12],"become":[8],"very":[9],"popular":[10,120],"and":[11,78,96,129,170],"achieved":[13],"great":[14],"success":[15],"in":[16,23,144],"many":[17,32],"computer":[18],"vision":[19],"tasks":[20],"-":[21],"particularly":[22],"object":[24,123,173],"recognition.":[25,174],"Partially":[26],"inspired":[27],"by":[28],"neuroscience,":[29],"CNNs":[30,93],"share":[31],"properties":[33],"with":[34,94,113,162,167],"the":[35,39,42,59,103,107,133,136,147,149,156],"visual":[36],"system":[37],"of":[38,44,54,71,135,146],"brain.":[40],"However,":[41],"filters":[43,70,98,110,161],"convolutional":[45],"layers":[46],"play":[47],"a":[48],"vital":[49],"role":[50],"on":[51,118,155],"overall":[52,104],"accuracy":[53],"CNNs.":[55],"this":[57],"paper,":[58],"Cellular":[60],"Simultaneous":[61],"Recurrent":[62],"(CSRNs)":[64],"are":[65,84,99],"applied":[66],"to":[67,101,131,165],"generate":[68],"initial":[69],"(CNs)":[74],"for":[75,86,122,172],"features":[76,158],"extraction":[77],"Regularized":[79],"Extreme":[80],"Learning":[81],"Machines":[82],"(RELM)":[83],"used":[85],"classification.":[87],"Furthermore,":[88],"Deep":[89],"Belief":[90],"(DBN),":[92],"random":[95,169],"Gabor":[97],"implemented":[100],"evaluate":[102,132],"performance":[105,134,154],"against":[106],"proposed":[108,137,150],"CSRN's":[109,160],"based":[111],"CNs":[112,163],"RELM.":[114],"Experiments":[115],"were":[116],"conducted":[117],"three":[119],"datasets":[121],"recognition":[124],"(such":[125],"as":[126],"face,":[127],"pedestrian,":[128],"car)":[130],"system.":[138],"The":[139],"experimental":[140],"results":[141],"show":[142],"that":[143],"most":[145],"cases,":[148],"approach":[151],"provides":[152],"better":[153],"extracted":[157],"using":[159],"compare":[164],"initialize":[166],"Gaussian":[168],"DBN":[171]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":8},{"year":2018,"cited_by_count":3},{"year":2016,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
