{"id":"https://openalex.org/W2510733224","doi":"https://doi.org/10.1109/icip.2016.7533051","title":"Ceci n'est pas une pipe: A deep convolutional network for fine-art paintings classification","display_name":"Ceci n'est pas une pipe: A deep convolutional network for fine-art paintings classification","publication_year":2016,"publication_date":"2016-08-17","ids":{"openalex":"https://openalex.org/W2510733224","doi":"https://doi.org/10.1109/icip.2016.7533051","mag":"2510733224"},"language":"fr","primary_location":{"id":"doi:10.1109/icip.2016.7533051","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2016.7533051","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 Image Processing (ICIP)","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/A5027004576","display_name":"Wei Tan","orcid":"https://orcid.org/0000-0003-0024-8009"},"institutions":[{"id":"https://openalex.org/I137975476","display_name":"Shinshu University","ror":"https://ror.org/0244rem06","country_code":"JP","type":"education","lineage":["https://openalex.org/I137975476"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Wei Ren Tan","raw_affiliation_strings":["Faculty of Engineering, Shinshu University, Nagano, Japan"],"affiliations":[{"raw_affiliation_string":"Faculty of Engineering, Shinshu University, Nagano, Japan","institution_ids":["https://openalex.org/I137975476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070805897","display_name":"Chee Seng Chan","orcid":"https://orcid.org/0000-0001-7677-2865"},"institutions":[{"id":"https://openalex.org/I33849332","display_name":"University of Malaya","ror":"https://ror.org/00rzspn62","country_code":"MY","type":"education","lineage":["https://openalex.org/I33849332"]}],"countries":["MY"],"is_corresponding":false,"raw_author_name":"Chee Seng Chan","raw_affiliation_strings":["Universiti Malaya, Kuala Lumpur, Wilayah Persekutuan, MY"],"affiliations":[{"raw_affiliation_string":"Universiti Malaya, Kuala Lumpur, Wilayah Persekutuan, MY","institution_ids":["https://openalex.org/I33849332"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036763177","display_name":"Hern\u00e1n Aguirre","orcid":"https://orcid.org/0000-0003-4480-1339"},"institutions":[{"id":"https://openalex.org/I137975476","display_name":"Shinshu University","ror":"https://ror.org/0244rem06","country_code":"JP","type":"education","lineage":["https://openalex.org/I137975476"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Hernan E. Aguirre","raw_affiliation_strings":["Faculty of Engineering, Shinshu University, Nagano, Japan"],"affiliations":[{"raw_affiliation_string":"Faculty of Engineering, Shinshu University, Nagano, Japan","institution_ids":["https://openalex.org/I137975476"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101441960","display_name":"Kiyoshi Tanaka","orcid":"https://orcid.org/0000-0003-2174-6015"},"institutions":[{"id":"https://openalex.org/I137975476","display_name":"Shinshu University","ror":"https://ror.org/0244rem06","country_code":"JP","type":"education","lineage":["https://openalex.org/I137975476"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Kiyoshi Tanaka","raw_affiliation_strings":["Faculty of Engineering, Shinshu University, Nagano, Japan"],"affiliations":[{"raw_affiliation_string":"Faculty of Engineering, Shinshu University, Nagano, Japan","institution_ids":["https://openalex.org/I137975476"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5027004576"],"corresponding_institution_ids":["https://openalex.org/I137975476"],"apc_list":null,"apc_paid":null,"fwci":8.2813,"has_fulltext":false,"cited_by_count":195,"citation_normalized_percentile":{"value":0.98260063,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"3703","last_page":"3707"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12650","display_name":"Aesthetic Perception and Analysis","score":0.9986000061035156,"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/T12650","display_name":"Aesthetic Perception and Analysis","score":0.9986000061035156,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9824000000953674,"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/T12981","display_name":"Conservation Techniques and Studies","score":0.9793999791145325,"subfield":{"id":"https://openalex.org/subfields/1206","display_name":"Conservation"},"field":{"id":"https://openalex.org/fields/12","display_name":"Arts and Humanities"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/painting","display_name":"Painting","score":0.6067250967025757},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6021271347999573},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4629557728767395},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3791644275188446},{"id":"https://openalex.org/keywords/art","display_name":"Art","score":0.21105849742889404},{"id":"https://openalex.org/keywords/art-history","display_name":"Art history","score":0.10741880536079407}],"concepts":[{"id":"https://openalex.org/C205783811","wikidata":"https://www.wikidata.org/wiki/Q11629","display_name":"Painting","level":2,"score":0.6067250967025757},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6021271347999573},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4629557728767395},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3791644275188446},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.21105849742889404},{"id":"https://openalex.org/C52119013","wikidata":"https://www.wikidata.org/wiki/Q50637","display_name":"Art history","level":1,"score":0.10741880536079407}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip.2016.7533051","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2016.7533051","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 Image Processing (ICIP)","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":51,"referenced_works":["https://openalex.org/W300217873","https://openalex.org/W639708223","https://openalex.org/W1622449098","https://openalex.org/W1686810756","https://openalex.org/W1849277567","https://openalex.org/W1924619199","https://openalex.org/W2011615896","https://openalex.org/W2031489346","https://openalex.org/W2057624659","https://openalex.org/W2059271241","https://openalex.org/W2061815253","https://openalex.org/W2062118960","https://openalex.org/W2097117768","https://openalex.org/W2108240927","https://openalex.org/W2117539524","https://openalex.org/W2128901179","https://openalex.org/W2128907386","https://openalex.org/W2134670479","https://openalex.org/W2149933564","https://openalex.org/W2155541015","https://openalex.org/W2155893237","https://openalex.org/W2161381512","https://openalex.org/W2161753062","https://openalex.org/W2163605009","https://openalex.org/W2164503390","https://openalex.org/W2179352600","https://openalex.org/W2209882149","https://openalex.org/W2613718673","https://openalex.org/W2962883796","https://openalex.org/W2963674932","https://openalex.org/W2963801405","https://openalex.org/W2963920537","https://openalex.org/W2964332173","https://openalex.org/W3098722327","https://openalex.org/W3102353939","https://openalex.org/W3118608800","https://openalex.org/W4294375521","https://openalex.org/W4299518610","https://openalex.org/W6610818398","https://openalex.org/W6620707391","https://openalex.org/W6636751772","https://openalex.org/W6637373629","https://openalex.org/W6640174519","https://openalex.org/W6653468076","https://openalex.org/W6674914833","https://openalex.org/W6679792166","https://openalex.org/W6682132143","https://openalex.org/W6682778277","https://openalex.org/W6684191040","https://openalex.org/W6765897598","https://openalex.org/W6787972765"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2580687016","https://openalex.org/W2886265999","https://openalex.org/W2383951830","https://openalex.org/W1591565242","https://openalex.org/W2369092230","https://openalex.org/W2357187602","https://openalex.org/W2940819518"],"abstract_inverted_index":{"\u201cCeci":[0],"n'est":[1],"pas":[2],"une":[3],"pipe\u201d":[4],"French":[5],"for":[6],"\u201cThis":[7],"is":[8,13,34,54,124,137,158,176],"not":[9,35,40,55],"a":[10,36,56,63,70,125,155,161,178],"pipe\u201d.":[11],"This":[12,136],"the":[14,18,22,42,52,79,102,105,114,141,184,191,195],"description":[15],"painted":[16],"on":[17,72],"first":[19],"painting":[20,33,53,110],"in":[21,108,129,169,217],"figure":[23],"above.":[24],"But":[25],"to":[26,41,93,100,131,151,166,173,186],"most":[27],"of":[28,62,75,104,121,140,205],"us,":[29],"how":[30],"could":[31],"this":[32,66],"pipe,":[37,57],"at":[38],"least":[39],"great":[43],"Belgian":[44],"surrealist":[45],"artist":[46],"Rene":[47],"Magritte.":[48],"He":[49],"said":[50],"that":[51,119,159,203],"but":[58],"rather":[59],"an":[60,95],"image":[61],"pipe.":[64],"In":[65,190],"paper,":[67],"we":[68,90,117,193],"present":[69],"study":[71],"large-scale":[73,199],"classification":[74,111,120],"fine-art":[76,109,122],"paintings":[77,209],"using":[78],"Deep":[80],"Convolutional":[81],"Network.":[82],"Our":[83],"objectives":[84],"are":[85,143],"two-folds.":[86],"On":[87,113],"one":[88],"hand,":[89,116],"would":[91],"like":[92],"train":[94,177],"end-to-end":[96],"deep":[97,106,179],"convolution":[98],"model":[99,107,180],"investigate":[101],"capability":[103],"problem.":[112],"other":[115],"argue":[118],"collections":[123],"more":[126,206],"challenging":[127],"problem":[128],"comparison":[130],"objects":[132],"or":[133,164],"face":[134],"recognition.":[135],"because":[138],"some":[139],"artworks":[142],"non-representational":[144],"nor":[145],"figurative,":[146],"and":[147,181,210],"might":[148],"requires":[149],"imagination":[150],"recognize":[152],"them.":[153],"Hence,":[154],"question":[156],"arose":[157],"does":[160],"machine":[162],"have":[163],"able":[165],"capture":[167],"\u201cimagination\u201d":[168],"paintings?":[170],"One":[171],"way":[172],"find":[174],"out":[175],"then":[182],"visualize":[183],"low-level":[185],"high-level":[187],"features":[188],"learnt.":[189],"experiment,":[192],"employed":[194],"recently":[196],"publicly":[197],"available":[198],"\u201cWikiart":[200],"paintings\u201d":[201],"dataset":[202],"consists":[204],"than":[207],"80,000":[208],"our":[211],"solution":[212],"achieved":[213],"state-of-the-art":[214],"results":[215],"(68%)":[216],"overall":[218],"performance.":[219]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":14},{"year":2024,"cited_by_count":13},{"year":2023,"cited_by_count":22},{"year":2022,"cited_by_count":36},{"year":2021,"cited_by_count":32},{"year":2020,"cited_by_count":24},{"year":2019,"cited_by_count":27},{"year":2018,"cited_by_count":11},{"year":2017,"cited_by_count":12}],"updated_date":"2026-03-12T08:34:05.389933","created_date":"2025-10-10T00:00:00"}
