{"id":"https://openalex.org/W2978803196","doi":"https://doi.org/10.1109/ijcnn.2019.8852040","title":"Scene Recognition via Object-to-Scene Class Conversion: End-to-End Training","display_name":"Scene Recognition via Object-to-Scene Class Conversion: End-to-End Training","publication_year":2019,"publication_date":"2019-07-01","ids":{"openalex":"https://openalex.org/W2978803196","doi":"https://doi.org/10.1109/ijcnn.2019.8852040","mag":"2978803196"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2019.8852040","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2019.8852040","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 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/A5028558267","display_name":"Hongje Seong","orcid":"https://orcid.org/0000-0001-7221-409X"},"institutions":[{"id":"https://openalex.org/I193775966","display_name":"Yonsei University","ror":"https://ror.org/01wjejq96","country_code":"KR","type":"education","lineage":["https://openalex.org/I193775966"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Hongje Seong","raw_affiliation_strings":["School of Electrical and Electronic Engineering, Yonsei University, Seoul, South Korea"],"affiliations":[{"raw_affiliation_string":"School of Electrical and Electronic Engineering, Yonsei University, Seoul, South Korea","institution_ids":["https://openalex.org/I193775966"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112883472","display_name":"Junhyuk Hyun","orcid":null},"institutions":[{"id":"https://openalex.org/I193775966","display_name":"Yonsei University","ror":"https://ror.org/01wjejq96","country_code":"KR","type":"education","lineage":["https://openalex.org/I193775966"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Junhyuk Hyun","raw_affiliation_strings":["School of Electrical and Electronic Engineering, Yonsei University, Seoul, South Korea"],"affiliations":[{"raw_affiliation_string":"School of Electrical and Electronic Engineering, Yonsei University, Seoul, South Korea","institution_ids":["https://openalex.org/I193775966"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101042903","display_name":"Hyunbae Chang","orcid":null},"institutions":[{"id":"https://openalex.org/I193775966","display_name":"Yonsei University","ror":"https://ror.org/01wjejq96","country_code":"KR","type":"education","lineage":["https://openalex.org/I193775966"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Hyunbae Chang","raw_affiliation_strings":["School of Electrical and Electronic Engineering, Yonsei University, Seoul, South Korea"],"affiliations":[{"raw_affiliation_string":"School of Electrical and Electronic Engineering, Yonsei University, Seoul, South Korea","institution_ids":["https://openalex.org/I193775966"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101711271","display_name":"Suhyeon Lee","orcid":"https://orcid.org/0000-0003-1989-9004"},"institutions":[{"id":"https://openalex.org/I193775966","display_name":"Yonsei University","ror":"https://ror.org/01wjejq96","country_code":"KR","type":"education","lineage":["https://openalex.org/I193775966"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Suhyeon Lee","raw_affiliation_strings":["School of Electrical and Electronic Engineering, Yonsei University, Seoul, South Korea"],"affiliations":[{"raw_affiliation_string":"School of Electrical and Electronic Engineering, Yonsei University, Seoul, South Korea","institution_ids":["https://openalex.org/I193775966"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112608015","display_name":"Suhan Woo","orcid":"https://orcid.org/0009-0008-1947-750X"},"institutions":[{"id":"https://openalex.org/I193775966","display_name":"Yonsei University","ror":"https://ror.org/01wjejq96","country_code":"KR","type":"education","lineage":["https://openalex.org/I193775966"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Suhan Woo","raw_affiliation_strings":["School of Electrical and Electronic Engineering, Yonsei University, Seoul, South Korea"],"affiliations":[{"raw_affiliation_string":"School of Electrical and Electronic Engineering, Yonsei University, Seoul, South Korea","institution_ids":["https://openalex.org/I193775966"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5065415014","display_name":"Euntai Kim","orcid":"https://orcid.org/0000-0002-0975-8390"},"institutions":[{"id":"https://openalex.org/I193775966","display_name":"Yonsei University","ror":"https://ror.org/01wjejq96","country_code":"KR","type":"education","lineage":["https://openalex.org/I193775966"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Euntai Kim","raw_affiliation_strings":["School of Electrical and Electronic Engineering, Yonsei University, Seoul, South Korea"],"affiliations":[{"raw_affiliation_string":"School of Electrical and Electronic Engineering, Yonsei University, Seoul, South Korea","institution_ids":["https://openalex.org/I193775966"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5028558267"],"corresponding_institution_ids":["https://openalex.org/I193775966"],"apc_list":null,"apc_paid":null,"fwci":1.0122,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":{"value":0.80971168,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":93,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9998999834060669,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9998999834060669,"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":0.9990000128746033,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9987000226974487,"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":0.8078457117080688},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7575854659080505},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.7100580930709839},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.6459493637084961},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6376400589942932},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6315876245498657},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.613582968711853},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5906904339790344},{"id":"https://openalex.org/keywords/cognitive-neuroscience-of-visual-object-recognition","display_name":"Cognitive neuroscience of visual object recognition","score":0.5274850726127625},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.4966612458229065},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.472903847694397},{"id":"https://openalex.org/keywords/end-to-end-principle","display_name":"End-to-end principle","score":0.4623355567455292},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4510868191719055},{"id":"https://openalex.org/keywords/layer","display_name":"Layer (electronics)","score":0.4489634335041046}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8078457117080688},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7575854659080505},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.7100580930709839},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.6459493637084961},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6376400589942932},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6315876245498657},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.613582968711853},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5906904339790344},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.5274850726127625},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.4966612458229065},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.472903847694397},{"id":"https://openalex.org/C74296488","wikidata":"https://www.wikidata.org/wiki/Q2527392","display_name":"End-to-end principle","level":2,"score":0.4623355567455292},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4510868191719055},{"id":"https://openalex.org/C2779227376","wikidata":"https://www.wikidata.org/wiki/Q6505497","display_name":"Layer (electronics)","level":2,"score":0.4489634335041046},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn.2019.8852040","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2019.8852040","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/15","display_name":"Life in Land","score":0.49000000953674316},{"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities","score":0.4000000059604645}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":52,"referenced_works":["https://openalex.org/W300523764","https://openalex.org/W1491719799","https://openalex.org/W1522301498","https://openalex.org/W1836465849","https://openalex.org/W2017814585","https://openalex.org/W2087164515","https://openalex.org/W2087347434","https://openalex.org/W2099528205","https://openalex.org/W2106097867","https://openalex.org/W2112019442","https://openalex.org/W2117539524","https://openalex.org/W2124372976","https://openalex.org/W2132093718","https://openalex.org/W2134670479","https://openalex.org/W2152161678","https://openalex.org/W2162915993","https://openalex.org/W2163605009","https://openalex.org/W2165698076","https://openalex.org/W2194775991","https://openalex.org/W2258484932","https://openalex.org/W2339172597","https://openalex.org/W2475223347","https://openalex.org/W2527800741","https://openalex.org/W2588591728","https://openalex.org/W2622263826","https://openalex.org/W2718724383","https://openalex.org/W2732026016","https://openalex.org/W2751703647","https://openalex.org/W2752782242","https://openalex.org/W2755125693","https://openalex.org/W2766736793","https://openalex.org/W2786339753","https://openalex.org/W2791186434","https://openalex.org/W2791754844","https://openalex.org/W2809273606","https://openalex.org/W2885419454","https://openalex.org/W2899771611","https://openalex.org/W2963420686","https://openalex.org/W2963446712","https://openalex.org/W2964121744","https://openalex.org/W3104752576","https://openalex.org/W3105023039","https://openalex.org/W3105178129","https://openalex.org/W4289388289","https://openalex.org/W6631190155","https://openalex.org/W6638667902","https://openalex.org/W6679792166","https://openalex.org/W6684191040","https://openalex.org/W6703720303","https://openalex.org/W6739622702","https://openalex.org/W6752840867","https://openalex.org/W6756040250"],"related_works":["https://openalex.org/W2975200075","https://openalex.org/W2200925278","https://openalex.org/W2613077666","https://openalex.org/W2363840281","https://openalex.org/W2360875750","https://openalex.org/W1837097281","https://openalex.org/W2143500446","https://openalex.org/W2574146284","https://openalex.org/W4206120980","https://openalex.org/W2801801420"],"abstract_inverted_index":{"When":[0],"a":[1,45,56,120],"person":[2],"recognize":[3,112],"the":[4,92,149,159],"scene":[5,53,73,126],"of":[6,26,67,78,87,151],"an":[7],"image,":[8],"contextual":[9],"understanding":[10,25],"from":[11],"its":[12],"environmental":[13,18,35],"elements":[14,19,36],"is":[15,128,156,168],"necessary.":[16],"These":[17],"are":[20,31,90,109],"variant":[21],"and":[22,63,83,101,139],"require":[23],"comprehensive":[24],"various":[27],"situations.":[28],"Especially,":[29],"objects":[30,62],"frequently":[32],"used":[33],"as":[34],"related":[37],"with":[38,55,76,135],"scene.":[39,64],"In":[40],"this":[41,117],"paper,":[42],"we":[43],"suggest":[44],"score":[46],"level":[47],"Class":[48],"Conversion":[49],"Matrix":[50],"(CCM)":[51],"for":[52],"recognition":[54,74],"great":[57],"focus":[58],"on":[59,144],"relationship":[60,80],"between":[61,81],"A":[65],"lot":[66],"existing":[68,160],"methods":[69,89],"have":[70],"already":[71],"build":[72],"systems":[75],"consideration":[77],"close":[79],"object":[82,93,107,123],"scenes.":[84],"However,":[85],"most":[86],"these":[88,106],"using":[91],"features":[94,108],"directly":[95],"without":[96],"any":[97],"conversions":[98],"or":[99],"reconstructions,":[100],"it":[102,155],"lack":[103],"confirmation":[104],"whether":[105],"helpful":[110],"to":[111,125,158],"scenes":[113],"correctly.":[114],"To":[115],"solve":[116],"problem,":[118],"CCM,":[119],"matrix":[121],"converting":[122],"feature":[124],"feature,":[127],"suggested.":[129],"Moreover,":[130],"CCM":[131],"can":[132],"be":[133],"implemented":[134],"neural":[136,163],"network":[137,164],"layer":[138],"end-to-end":[140],"trainable.":[141],"Extensive":[142],"experiments":[143],"Places":[145],"2":[146],"dataset":[147],"demonstrate":[148],"effectiveness":[150],"our":[152],"approach,":[153],"when":[154],"applied":[157],"deep":[161],"convolutional":[162],"architectures.":[165],"The":[166],"code":[167],"available":[169],"at":[170],"https://github.com/Hongje/Class_Conversion_Matrix-Places365":[171]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
