{"id":"https://openalex.org/W2398083795","doi":"https://doi.org/10.1109/icassp.2016.7471892","title":"Modeling deep bidirectional relationships for image classification and generation","display_name":"Modeling deep bidirectional relationships for image classification and generation","publication_year":2016,"publication_date":"2016-03-01","ids":{"openalex":"https://openalex.org/W2398083795","doi":"https://doi.org/10.1109/icassp.2016.7471892","mag":"2398083795"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2016.7471892","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2016.7471892","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5041887072","display_name":"Toru Nakashika","orcid":"https://orcid.org/0000-0003-1863-6771"},"institutions":[{"id":"https://openalex.org/I20529979","display_name":"University of Electro-Communications","ror":"https://ror.org/02x73b849","country_code":"JP","type":"education","lineage":["https://openalex.org/I20529979"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Toru Nakashika","raw_affiliation_strings":["The Univeristy of Electro-Communications, Graduate School of Information Systems"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Univeristy of Electro-Communications, Graduate School of Information Systems","institution_ids":["https://openalex.org/I20529979"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009283470","display_name":"Tetsuya Takiguchi","orcid":"https://orcid.org/0000-0001-5005-7679"},"institutions":[{"id":"https://openalex.org/I65837984","display_name":"Kobe University","ror":"https://ror.org/03tgsfw79","country_code":"JP","type":"education","lineage":["https://openalex.org/I65837984"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Tetsuya Takiguchi","raw_affiliation_strings":["Kobe University, Graduate School of System Informatics"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kobe University, Graduate School of System Informatics","institution_ids":["https://openalex.org/I65837984"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5040766342","display_name":"Yasuo Ariki","orcid":"https://orcid.org/0000-0003-3473-2026"},"institutions":[{"id":"https://openalex.org/I65837984","display_name":"Kobe University","ror":"https://ror.org/03tgsfw79","country_code":"JP","type":"education","lineage":["https://openalex.org/I65837984"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yasuo Ariki","raw_affiliation_strings":["Kobe University, Graduate School of System Informatics"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kobe University, Graduate School of System Informatics","institution_ids":["https://openalex.org/I65837984"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.1006,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.34523354,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1327","last_page":"1331"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":1.0,"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/T11309","display_name":"Music and Audio Processing","score":0.9948999881744385,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T12357","display_name":"Digital Media Forensic Detection","score":0.9839000105857849,"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/boltzmann-machine","display_name":"Boltzmann machine","score":0.9129392504692078},{"id":"https://openalex.org/keywords/deep-belief-network","display_name":"Deep belief network","score":0.7718400955200195},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7605923414230347},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6727632880210876},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.6618027091026306},{"id":"https://openalex.org/keywords/restricted-boltzmann-machine","display_name":"Restricted Boltzmann machine","score":0.657493531703949},{"id":"https://openalex.org/keywords/layer","display_name":"Layer (electronics)","score":0.6048136353492737},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6034255027770996},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.562623143196106},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5437982082366943},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.5353842973709106},{"id":"https://openalex.org/keywords/architecture","display_name":"Architecture","score":0.5299514532089233},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.4977889060974121},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.47418245673179626},{"id":"https://openalex.org/keywords/statistical-model","display_name":"Statistical model","score":0.43704527616500854},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.3294789493083954}],"concepts":[{"id":"https://openalex.org/C192576344","wikidata":"https://www.wikidata.org/wiki/Q194706","display_name":"Boltzmann machine","level":3,"score":0.9129392504692078},{"id":"https://openalex.org/C97385483","wikidata":"https://www.wikidata.org/wiki/Q16954980","display_name":"Deep belief network","level":3,"score":0.7718400955200195},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7605923414230347},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6727632880210876},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.6618027091026306},{"id":"https://openalex.org/C199354608","wikidata":"https://www.wikidata.org/wiki/Q7316287","display_name":"Restricted Boltzmann machine","level":3,"score":0.657493531703949},{"id":"https://openalex.org/C2779227376","wikidata":"https://www.wikidata.org/wiki/Q6505497","display_name":"Layer (electronics)","level":2,"score":0.6048136353492737},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6034255027770996},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.562623143196106},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5437982082366943},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.5353842973709106},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.5299514532089233},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.4977889060974121},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.47418245673179626},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.43704527616500854},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.3294789493083954},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0},{"id":"https://openalex.org/C153349607","wikidata":"https://www.wikidata.org/wiki/Q36649","display_name":"Visual arts","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp.2016.7471892","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2016.7471892","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5600000023841858,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W177847060","https://openalex.org/W189596042","https://openalex.org/W1813659000","https://openalex.org/W1993882792","https://openalex.org/W2040370888","https://openalex.org/W2075505763","https://openalex.org/W2136922672","https://openalex.org/W2139671364","https://openalex.org/W2161893161","https://openalex.org/W2185528074","https://openalex.org/W2294351487","https://openalex.org/W2399803916","https://openalex.org/W2953267151","https://openalex.org/W6607232846","https://openalex.org/W6607775107","https://openalex.org/W6638304892","https://openalex.org/W6680067488","https://openalex.org/W6683819664"],"related_works":["https://openalex.org/W2064630666","https://openalex.org/W3121598771","https://openalex.org/W2287713958","https://openalex.org/W3010338767","https://openalex.org/W2513801676","https://openalex.org/W2916681395","https://openalex.org/W1257380361","https://openalex.org/W3005559199","https://openalex.org/W2133034788","https://openalex.org/W2892911634"],"abstract_inverted_index":{"This":[0,122],"paper":[1,123],"presents":[2,124],"a":[3,9,17,21,86,107,119],"novel":[4],"probabilistic":[5,120],"model":[6,24,27],"that":[7],"represents":[8],"joint":[10],"probability":[11],"of":[12],"two":[13,60,79],"visible":[14,33,38,80],"variables":[15,81],"with":[16,46],"deep":[18,22,52,96,99],"architecture,":[19],"called":[20],"relational":[23],"(DRM).":[25],"The":[26],"stacks":[28],"several":[29],"layers":[30,42,62],"from":[31],"one":[32],"layer":[34],"on":[35],"to":[36,73,94,130],"another":[37],"layer,":[39],"sandwiching":[40],"hidden":[41],"between":[43,59,78],"them.":[44],"As":[45],"restricted":[47],"Boltzmann":[48,53],"machines":[49,54],"(RBMs)":[50],"and":[51,89,111,125,137],"(DBMs),":[55],"all":[56],"connections":[57],"(weights)":[58],"adjacent":[61],"are":[63],"undirected.":[64],"During":[65],"the":[66,70,103,113,127],"maximum-likelihood":[67],"(ML)-based":[68],"training,":[69],"network":[71],"attempts":[72],"capture":[74],"latent":[75],"complex":[76],"relationships":[77],"(e.g.,":[82],"an":[83],"image":[84],"showing":[85],"certain":[87],"number":[88],"its":[90,95],"corresponding":[91],"label)":[92],"thanks":[93],"architecture.":[97],"Unlike":[98],"neural":[100],"networks,":[101],"1)":[102],"proposed":[104],"DRM":[105],"is":[106],"totally":[108],"generative":[109],"model,":[110],"2)":[112],"weights":[114],"can":[115],"be":[116],"optimized":[117],"in":[118,135],"manner.":[121],"discusses":[126],"experiments":[128],"conduced":[129],"evaluate":[131],"our":[132],"DRM's":[133],"performance":[134],"recognition":[136],"generation":[138],"tasks.":[139]},"counts_by_year":[{"year":2018,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}