{"id":"https://openalex.org/W4214942583","doi":"https://doi.org/10.1109/access.2022.3155873","title":"Hybrid Restricted Boltzmann Machine\u2013 Convolutional Neural Network Model for Image Recognition","display_name":"Hybrid Restricted Boltzmann Machine\u2013 Convolutional Neural Network Model for Image Recognition","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4214942583","doi":"https://doi.org/10.1109/access.2022.3155873"},"language":"en","primary_location":{"id":"doi:10.1109/access.2022.3155873","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3155873","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9668973/09724261.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/9668973/09724261.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5103010199","display_name":"Szymon Sobczak","orcid":"https://orcid.org/0000-0002-0004-9491"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Szymon Sobczak","raw_affiliation_strings":["Institute of Automatic Control and Robotics, Pozna&#x0144; University of Technology, Pozna&#x0144;, Poland"],"raw_orcid":"https://orcid.org/0000-0002-0004-9491","affiliations":[{"raw_affiliation_string":"Institute of Automatic Control and Robotics, Pozna&#x0144; University of Technology, Pozna&#x0144;, Poland","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5073015442","display_name":"Rafa\u0142 Kapela","orcid":"https://orcid.org/0000-0002-0624-7608"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Rafal Kapela","raw_affiliation_strings":["Institute of Automatic Control and Robotics, Pozna&#x0144; University of Technology, Pozna&#x0144;, Poland"],"raw_orcid":"https://orcid.org/0000-0002-0624-7608","affiliations":[{"raw_affiliation_string":"Institute of Automatic Control and Robotics, Pozna&#x0144; University of Technology, Pozna&#x0144;, Poland","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.2624,"has_fulltext":true,"cited_by_count":3,"citation_normalized_percentile":{"value":0.58482411,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"10","issue":null,"first_page":"24985","last_page":"24994"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9998999834060669,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9998999834060669,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9995999932289124,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9994000196456909,"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/computer-science","display_name":"Computer science","score":0.8386458158493042},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6458780169487},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6217026114463806},{"id":"https://openalex.org/keywords/restricted-boltzmann-machine","display_name":"Restricted Boltzmann machine","score":0.5600273013114929},{"id":"https://openalex.org/keywords/boltzmann-machine","display_name":"Boltzmann machine","score":0.5600021481513977},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5276612043380737},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5096702575683594},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.504817545413971},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5019922256469727},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.44924020767211914},{"id":"https://openalex.org/keywords/layer","display_name":"Layer (electronics)","score":0.43988245725631714},{"id":"https://openalex.org/keywords/binary-number","display_name":"Binary number","score":0.43376898765563965},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.42343008518218994},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4186588525772095},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.41481202840805054},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.40842652320861816},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3704095482826233}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8386458158493042},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6458780169487},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6217026114463806},{"id":"https://openalex.org/C199354608","wikidata":"https://www.wikidata.org/wiki/Q7316287","display_name":"Restricted Boltzmann machine","level":3,"score":0.5600273013114929},{"id":"https://openalex.org/C192576344","wikidata":"https://www.wikidata.org/wiki/Q194706","display_name":"Boltzmann machine","level":3,"score":0.5600021481513977},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5276612043380737},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5096702575683594},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.504817545413971},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5019922256469727},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.44924020767211914},{"id":"https://openalex.org/C2779227376","wikidata":"https://www.wikidata.org/wiki/Q6505497","display_name":"Layer (electronics)","level":2,"score":0.43988245725631714},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.43376898765563965},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.42343008518218994},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4186588525772095},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.41481202840805054},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.40842652320861816},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3704095482826233},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2022.3155873","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3155873","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9668973/09724261.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:3fe755f4650a4ed981f9908a2dbb631f","is_oa":true,"landing_page_url":"https://doaj.org/article/3fe755f4650a4ed981f9908a2dbb631f","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 10, Pp 24985-24994 (2022)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2022.3155873","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3155873","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9668973/09724261.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","score":0.5099999904632568,"display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4214942583.pdf","grobid_xml":"https://content.openalex.org/works/W4214942583.grobid-xml"},"referenced_works_count":58,"referenced_works":["https://openalex.org/W44815768","https://openalex.org/W177847060","https://openalex.org/W1490682695","https://openalex.org/W1515020792","https://openalex.org/W1813659000","https://openalex.org/W1945616565","https://openalex.org/W1980073965","https://openalex.org/W1982366717","https://openalex.org/W1982968190","https://openalex.org/W1986803802","https://openalex.org/W2009701012","https://openalex.org/W2009927598","https://openalex.org/W2010526455","https://openalex.org/W2042492924","https://openalex.org/W2047643928","https://openalex.org/W2078626246","https://openalex.org/W2095705004","https://openalex.org/W2099866409","https://openalex.org/W2100495367","https://openalex.org/W2136922672","https://openalex.org/W2152161678","https://openalex.org/W2172174689","https://openalex.org/W2194775991","https://openalex.org/W2294798173","https://openalex.org/W2319660501","https://openalex.org/W2612786451","https://openalex.org/W2618530766","https://openalex.org/W2767547957","https://openalex.org/W2896050332","https://openalex.org/W2963218601","https://openalex.org/W2963446712","https://openalex.org/W2973498290","https://openalex.org/W2982859738","https://openalex.org/W2988533489","https://openalex.org/W2988916019","https://openalex.org/W2996364564","https://openalex.org/W3038988173","https://openalex.org/W3140854437","https://openalex.org/W3156867879","https://openalex.org/W3157506437","https://openalex.org/W3169839597","https://openalex.org/W3173101542","https://openalex.org/W3195438473","https://openalex.org/W3204609915","https://openalex.org/W3217536461","https://openalex.org/W4231109964","https://openalex.org/W4287822843","https://openalex.org/W4313156423","https://openalex.org/W6607232846","https://openalex.org/W6637373629","https://openalex.org/W6638444622","https://openalex.org/W6640425456","https://openalex.org/W6640963894","https://openalex.org/W6674330103","https://openalex.org/W6677919164","https://openalex.org/W6775600506","https://openalex.org/W6795140394","https://openalex.org/W6803870738"],"related_works":["https://openalex.org/W2952018105","https://openalex.org/W2916681395","https://openalex.org/W4283272532","https://openalex.org/W2119341610","https://openalex.org/W2556473569","https://openalex.org/W2193475944","https://openalex.org/W4302433642","https://openalex.org/W2529583158","https://openalex.org/W2551541394","https://openalex.org/W2892911634"],"abstract_inverted_index":{"Convolutional":[0],"Neural":[1],"Networks":[2],"(CNNs)":[3],"have":[4],"become":[5],"a":[6,81,118,127,135,143],"standard":[7],"approach":[8],"to":[9,22,80,108,112,175,183,191],"many":[10,35],"image":[11,184],"processing":[12],"dilemmas.":[13],"Consequently,":[14],"most":[15],"of":[16,34,75,90,101,153],"the":[17,24,88,104,115,123,151,157,169],"proposed":[18],"CNN":[19,91],"architectures":[20,56],"tend":[21],"increase":[23],"model":[25],"deepness":[26],"or":[27,55,92],"layer":[28,85,98],"complexity.":[29,96],"Thus,":[30],"they":[31],"are":[32],"composed":[33,100],"parameters":[36],"and":[37,42,131],"need":[38],"considerable":[39],"computing":[40],"resources":[41],"training":[43,154],"examples.":[44],"However,":[45],"some":[46],"recent":[47],"works":[48],"show":[49,167],"that":[50,86,121,145,168],"either":[51],"shallow":[52],"neural":[53,119],"networks":[54],"without":[57],"convolutions":[58],"can":[59],"achieve":[60],"similar":[61],"results":[62],"with":[63,71,156],"these":[64,76],"models":[65],"often":[66],"being":[67],"used":[68,107,148],"in":[69,134],"systems":[70],"limited":[72],"resources.":[73],"Consideration":[74],"aspects":[77],"led":[78],"us":[79],"relatively":[82],"simple":[83],"preprocessing":[84],"increases":[87],"accuracy":[89,177],"may":[93,146],"reduce":[94],"its":[95],"The":[97],"is":[99,106,117,132,179],"two":[102],"parts:":[103],"first":[105],"transform":[109],"RGB":[110],"data":[111,125],"binary":[113,124],"representation,":[114],"second":[116],"network":[120],"transforms":[122],"into":[126],"multi-channel,":[128],"real-value":[129],"matrix":[130],"trained":[133],"fully":[136],"unsupervised":[137],"manner.":[138],"Our":[139,165],"proposal":[140],"also":[141,180],"includes":[142],"metric":[144],"be":[147],"for":[149],"measuring":[150],"similarity":[152],"data,":[155],"latter":[158],"proving":[159],"useful":[160],"when":[161,189],"performing":[162],"transfer":[163],"learning.":[164],"experiments":[166],"resulting":[170],"architecture":[171],"not":[172],"only":[173],"helps":[174],"improve":[176],"but":[178],"more":[181],"robust":[182],"noise,":[185],"including":[186],"adversarial":[187],"attacks,":[188],"compared":[190],"state-of-the-art":[192],"models.":[193]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
