{"id":"https://openalex.org/W3203750789","doi":"https://doi.org/10.1109/access.2021.3115942","title":"Very Deep Learning-Based Illumination Estimation Approach With Cascading Residual Network Architecture (CRNA)","display_name":"Very Deep Learning-Based Illumination Estimation Approach With Cascading Residual Network Architecture (CRNA)","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W3203750789","doi":"https://doi.org/10.1109/access.2021.3115942","mag":"3203750789"},"language":"en","primary_location":{"id":"doi:10.1109/access.2021.3115942","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3115942","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09548902.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/ielx7/6287639/6514899/09548902.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5045054519","display_name":"Ho-Hyoung Choi","orcid":null},"institutions":[{"id":"https://openalex.org/I31419693","display_name":"Kyungpook National University","ror":"https://ror.org/040c17130","country_code":"KR","type":"education","lineage":["https://openalex.org/I31419693"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Ho-Hyoung Choi","raw_affiliation_strings":["Advanced Dental Device Development Institute, School of Dentistry, Kyungpook National University, 2177, Dalgubeol-daero, Jung-gu, Daegu 41940, Korea. (e-mail: chhman2000@msn.com)","School of Dentistry, Advanced Dental Device Development Institute, Kyungpook National University, Jung-gu, Daegu, South Korea"],"raw_orcid":"https://orcid.org/0000-0001-6843-3556","affiliations":[{"raw_affiliation_string":"Advanced Dental Device Development Institute, School of Dentistry, Kyungpook National University, 2177, Dalgubeol-daero, Jung-gu, Daegu 41940, Korea. (e-mail: chhman2000@msn.com)","institution_ids":["https://openalex.org/I31419693"]},{"raw_affiliation_string":"School of Dentistry, Advanced Dental Device Development Institute, Kyungpook National University, Jung-gu, Daegu, South Korea","institution_ids":["https://openalex.org/I31419693"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5018641732","display_name":"Byoung\u2010Ju Yun","orcid":"https://orcid.org/0000-0002-9898-2262"},"institutions":[{"id":"https://openalex.org/I31419693","display_name":"Kyungpook National University","ror":"https://ror.org/040c17130","country_code":"KR","type":"education","lineage":["https://openalex.org/I31419693"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Byoung-Ju Yun","raw_affiliation_strings":["School of Electronics Engineering, IT College, Kyungpook National University, 80, Daehak-ro, Buk-gu, Daegu 41566, Korea","School of Electronics Engineering, IT College, Kyungpook National University, Buk-gu, Daegu, South Korea"],"raw_orcid":"https://orcid.org/0000-0002-9898-2262","affiliations":[{"raw_affiliation_string":"School of Electronics Engineering, IT College, Kyungpook National University, 80, Daehak-ro, Buk-gu, Daegu 41566, Korea","institution_ids":["https://openalex.org/I31419693"]},{"raw_affiliation_string":"School of Electronics Engineering, IT College, Kyungpook National University, Buk-gu, Daegu, South Korea","institution_ids":["https://openalex.org/I31419693"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I31419693"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.748,"has_fulltext":true,"cited_by_count":8,"citation_normalized_percentile":{"value":0.71697893,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":"9","issue":null,"first_page":"133552","last_page":"133560"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11666","display_name":"Color Science and Applications","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/3107","display_name":"Atomic and Molecular Physics, and Optics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11666","display_name":"Color Science and Applications","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/3107","display_name":"Atomic and Molecular Physics, and Optics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11019","display_name":"Image Enhancement Techniques","score":0.9980999827384949,"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/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9941999912261963,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.8078899383544922},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7422029972076416},{"id":"https://openalex.org/keywords/residual-neural-network","display_name":"Residual neural network","score":0.5851414203643799},{"id":"https://openalex.org/keywords/architecture","display_name":"Architecture","score":0.5720617175102234},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5607558488845825},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.543310284614563},{"id":"https://openalex.org/keywords/estimation","display_name":"Estimation","score":0.41620516777038574},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.32663923501968384},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.15219324827194214},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.08828258514404297},{"id":"https://openalex.org/keywords/systems-engineering","display_name":"Systems engineering","score":0.07939055562019348}],"concepts":[{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.8078899383544922},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7422029972076416},{"id":"https://openalex.org/C2944601119","wikidata":"https://www.wikidata.org/wiki/Q43744058","display_name":"Residual neural network","level":3,"score":0.5851414203643799},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.5720617175102234},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5607558488845825},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.543310284614563},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.41620516777038574},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.32663923501968384},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.15219324827194214},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08828258514404297},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.07939055562019348},{"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}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2021.3115942","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3115942","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09548902.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:3f27c14a1538487682ed7e604bda731e","is_oa":true,"landing_page_url":"https://doaj.org/article/3f27c14a1538487682ed7e604bda731e","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 9, Pp 133552-133560 (2021)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2021.3115942","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3115942","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09548902.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":[],"awards":[{"id":"https://openalex.org/G2320710934","display_name":null,"funder_award_id":"NRF-2019R1I1A3A01061844","funder_id":"https://openalex.org/F4320322120","funder_display_name":"National Research Foundation of Korea"},{"id":"https://openalex.org/G3134391686","display_name":null,"funder_award_id":"NRF-2018R1D1A1B07040457","funder_id":"https://openalex.org/F4320322120","funder_display_name":"National Research Foundation of Korea"},{"id":"https://openalex.org/G3804926016","display_name":null,"funder_award_id":"NRF-2018R1D1A1B07040457","funder_id":"https://openalex.org/F4320320671","funder_display_name":"National Research Foundation"}],"funders":[{"id":"https://openalex.org/F4320320671","display_name":"National Research Foundation","ror":"https://ror.org/05s0g1g46"},{"id":"https://openalex.org/F4320322120","display_name":"National Research Foundation of Korea","ror":"https://ror.org/013aysd81"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3203750789.pdf","grobid_xml":"https://content.openalex.org/works/W3203750789.grobid-xml"},"referenced_works_count":54,"referenced_works":["https://openalex.org/W759139936","https://openalex.org/W1530411632","https://openalex.org/W1534426948","https://openalex.org/W1798160349","https://openalex.org/W1898616786","https://openalex.org/W1925897490","https://openalex.org/W1945748771","https://openalex.org/W1950407018","https://openalex.org/W1960752652","https://openalex.org/W1966855663","https://openalex.org/W1979423149","https://openalex.org/W1988091178","https://openalex.org/W2052090926","https://openalex.org/W2053354349","https://openalex.org/W2059511298","https://openalex.org/W2068294844","https://openalex.org/W2076205488","https://openalex.org/W2082538584","https://openalex.org/W2088828956","https://openalex.org/W2090412934","https://openalex.org/W2100001370","https://openalex.org/W2101752850","https://openalex.org/W2107558608","https://openalex.org/W2108303106","https://openalex.org/W2111963040","https://openalex.org/W2115257219","https://openalex.org/W2116278081","https://openalex.org/W2128059302","https://openalex.org/W2133593670","https://openalex.org/W2139698815","https://openalex.org/W2154264220","https://openalex.org/W2194775991","https://openalex.org/W2271840356","https://openalex.org/W2306965214","https://openalex.org/W2397711071","https://openalex.org/W2509601486","https://openalex.org/W2519060067","https://openalex.org/W2556952061","https://openalex.org/W2613546176","https://openalex.org/W2739489527","https://openalex.org/W2916633721","https://openalex.org/W2963645458","https://openalex.org/W2980419920","https://openalex.org/W3013758853","https://openalex.org/W3021960276","https://openalex.org/W3043630312","https://openalex.org/W3094266084","https://openalex.org/W3098971031","https://openalex.org/W3129236596","https://openalex.org/W4238032015","https://openalex.org/W6694517276","https://openalex.org/W6711909402","https://openalex.org/W6737993925","https://openalex.org/W6749061506"],"related_works":["https://openalex.org/W3196952692","https://openalex.org/W2984708981","https://openalex.org/W2755231872","https://openalex.org/W4300939921","https://openalex.org/W4383097772","https://openalex.org/W2964350391","https://openalex.org/W2274287116","https://openalex.org/W2897517148","https://openalex.org/W2983358626","https://openalex.org/W2964137095"],"abstract_inverted_index":{"For":[0],"the":[1,32,41,47,54,61,71,80,87,149,161,169,175,185,203,210,213,218,230,241,246],"imaging":[2],"signal":[3],"processing":[4],"(ISP)":[5],"pipeline":[6],"of":[7,13,50,74,82,111,138,212,223,245],"digital":[8],"image":[9,83],"devices,":[10],"it":[11],"is":[12,66,94,207],"high":[14],"significance":[15],"to":[16,67,97,121,133,143,188,196,209,216],"remove":[17],"undesirable":[18],"illuminant":[19,76],"effects":[20],"and":[21,53,171,200,225,236,239],"obtain":[22],"color":[23,29,34,100],"invariance,":[24],"commonly":[25],"known":[26],"as":[27,136],"\u2018computational":[28],"constancy\u2019.":[30],"Achieving":[31],"computational":[33,99],"constancy":[35],"requires":[36],"going":[37],"through":[38],"two":[39],"phases:":[40],"illumination":[42,64,150],"estimation,":[43],"which":[44,167],"will":[45],"be":[46],"primary":[48],"focus":[49],"this":[51,145,153],"work,":[52],"human":[55],"visual":[56],"perception-based":[57],"chromatic":[58],"adaptation.":[59],"At":[60],"first":[62],"phase,":[63],"estimation":[65,92,151],"predict":[68],"RGB":[69],"triplets,":[70],"numeric":[72],"representations":[73],"incident":[75],"colors,":[77],"by":[78],"calculating":[79],"values":[81],"pixels.":[84],"How":[85],"much":[86],"network":[88,179,187],"can":[89],"increase":[90],"its":[91],"accuracy":[93,120],"a":[95,109,130,156],"key":[96],"realizing":[98],"constancy.":[101],"With":[102],"recent":[103],"advances":[104],"in":[105,148,193],"deep":[106,112,158,176,250],"learning":[107,198,251],"(DL),":[108],"lot":[110],"learning-based":[113,159],"approaches":[114],"have":[115],"been":[116],"suggested,":[117],"bringing":[118],"higher":[119],"computer":[122],"vision":[123],"applications,":[124],"but":[125],"there":[126],"are":[127],"still":[128],"quite":[129],"few":[131],"obstacles":[132],"overcome":[134],"such":[135],"instability":[137],"learning.":[139],"In":[140],"an":[141],"attempt":[142],"address":[144],"ill-posed":[146],"problem":[147],"space,":[152],"article":[154],"presents":[155],"novel":[157],"approach,":[160],"Cascading":[162],"Residual":[163],"Network":[164],"Architecture":[165],"(CRNA),":[166],"incorporates":[168],"ResNet":[170],"cascading":[172,182,214],"mechanism":[173,183,215],"into":[174],"convolutional":[177],"neural":[178],"(DCNN).":[180],"The":[181],"helps":[184],"proposed":[186,231,247],"restrain":[189],"from":[190],"suddenly":[191],"varying":[192],"size,":[194],"serves":[195],"mitigate":[197],"instability,":[199],"thereby":[201],"reduces":[202],"quality":[204],"degradation.":[205],"This":[206],"attributed":[208],"ability":[211],"fine-tune":[217],"pre-trained":[219],"DCNN.":[220],"Considerable":[221],"amounts":[222],"datasets":[224],"comparative":[226],"experiments":[227],"highlight":[228],"that":[229],"approach":[232,248],"delivers":[233],"more":[234],"stable":[235],"robust":[237],"results":[238],"imply":[240],"potential":[242],"for":[243],"generalization":[244],"across":[249],"applications.":[252]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}