{"id":"https://openalex.org/W4389041965","doi":"https://doi.org/10.1109/csit61576.2023.10324137","title":"Test Images for Training Convolutional Neural Networks for Image Contrast Assessment","display_name":"Test Images for Training Convolutional Neural Networks for Image Contrast Assessment","publication_year":2023,"publication_date":"2023-10-19","ids":{"openalex":"https://openalex.org/W4389041965","doi":"https://doi.org/10.1109/csit61576.2023.10324137"},"language":"en","primary_location":{"id":"doi:10.1109/csit61576.2023.10324137","is_oa":false,"landing_page_url":"https://doi.org/10.1109/csit61576.2023.10324137","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE 18th International Conference on Computer Science and Information Technologies (CSIT)","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/A5033454791","display_name":"Arkadiusz Talun","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Arkadiusz Talun","raw_affiliation_strings":["Emplocity Ltd,Warsaw,Poland"],"affiliations":[{"raw_affiliation_string":"Emplocity Ltd,Warsaw,Poland","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077565916","display_name":"Pawe\u0142 Drozda","orcid":"https://orcid.org/0000-0003-3163-9408"},"institutions":[{"id":"https://openalex.org/I47996466","display_name":"University of Warmia and Mazury in Olsztyn","ror":"https://ror.org/05s4feg49","country_code":"PL","type":"education","lineage":["https://openalex.org/I47996466"]}],"countries":["PL"],"is_corresponding":false,"raw_author_name":"Pawel Drozda","raw_affiliation_strings":["University of Warmia and Mazury in Olsztyn,Olsztyn,Poland"],"affiliations":[{"raw_affiliation_string":"University of Warmia and Mazury in Olsztyn,Olsztyn,Poland","institution_ids":["https://openalex.org/I47996466"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030595904","display_name":"Yuriy Romanyshyn","orcid":"https://orcid.org/0000-0003-2794-432X"},"institutions":[{"id":"https://openalex.org/I98435010","display_name":"Lviv Polytechnic National University","ror":"https://ror.org/0542q3127","country_code":"UA","type":"education","lineage":["https://openalex.org/I98435010"]}],"countries":["UA"],"is_corresponding":false,"raw_author_name":"Yuriy Romanyshyn","raw_affiliation_strings":["Lviv Polytechnic National University,Lviv,Ukraine"],"affiliations":[{"raw_affiliation_string":"Lviv Polytechnic National University,Lviv,Ukraine","institution_ids":["https://openalex.org/I98435010"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5093346121","display_name":"Oles Tehlivets","orcid":null},"institutions":[{"id":"https://openalex.org/I98435010","display_name":"Lviv Polytechnic National University","ror":"https://ror.org/0542q3127","country_code":"UA","type":"education","lineage":["https://openalex.org/I98435010"]}],"countries":["UA"],"is_corresponding":false,"raw_author_name":"Oles Tehlivets","raw_affiliation_strings":["Lviv Polytechnic National University,Lviv,Ukraine"],"affiliations":[{"raw_affiliation_string":"Lviv Polytechnic National University,Lviv,Ukraine","institution_ids":["https://openalex.org/I98435010"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5047728012","display_name":"Sergei Yelmanov","orcid":"https://orcid.org/0000-0002-6097-9527"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sergei Yelmanov","raw_affiliation_strings":["Special Design Office of Television Systems,Lviv,Ukraine"],"affiliations":[{"raw_affiliation_string":"Special Design Office of Television Systems,Lviv,Ukraine","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5033454791"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.2305714,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11659","display_name":"Advanced Image Fusion Techniques","score":0.995199978351593,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11659","display_name":"Advanced Image Fusion Techniques","score":0.995199978351593,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11165","display_name":"Image and Video Quality Assessment","score":0.992900013923645,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9726999998092651,"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/convolutional-neural-network","display_name":"Convolutional neural network","score":0.8442032933235168},{"id":"https://openalex.org/keywords/contrast","display_name":"Contrast (vision)","score":0.7618607878684998},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.755718469619751},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7395539283752441},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.7164701223373413},{"id":"https://openalex.org/keywords/brightness","display_name":"Brightness","score":0.6006699800491333},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.588689386844635},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5565565824508667},{"id":"https://openalex.org/keywords/standard-test-image","display_name":"Standard test image","score":0.5534932613372803},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5300257802009583},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5166990756988525},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.2914700508117676}],"concepts":[{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.8442032933235168},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.7618607878684998},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.755718469619751},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7395539283752441},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.7164701223373413},{"id":"https://openalex.org/C125245961","wikidata":"https://www.wikidata.org/wiki/Q221656","display_name":"Brightness","level":2,"score":0.6006699800491333},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.588689386844635},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5565565824508667},{"id":"https://openalex.org/C180462255","wikidata":"https://www.wikidata.org/wiki/Q3559736","display_name":"Standard test image","level":4,"score":0.5534932613372803},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5300257802009583},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5166990756988525},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.2914700508117676},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/csit61576.2023.10324137","is_oa":false,"landing_page_url":"https://doi.org/10.1109/csit61576.2023.10324137","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE 18th International Conference on Computer Science and Information Technologies (CSIT)","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":15,"referenced_works":["https://openalex.org/W1974013408","https://openalex.org/W2158564760","https://openalex.org/W2219988151","https://openalex.org/W2748431992","https://openalex.org/W2748583036","https://openalex.org/W2777223338","https://openalex.org/W2793454839","https://openalex.org/W2915223083","https://openalex.org/W2979434101","https://openalex.org/W2982461593","https://openalex.org/W4229456138","https://openalex.org/W6684791271","https://openalex.org/W6743852547","https://openalex.org/W6745059213","https://openalex.org/W6749328836"],"related_works":["https://openalex.org/W2387055199","https://openalex.org/W2313061941","https://openalex.org/W2588661485","https://openalex.org/W1953485902","https://openalex.org/W2052546562","https://openalex.org/W2605640648","https://openalex.org/W3175896399","https://openalex.org/W4298119411","https://openalex.org/W4250745116","https://openalex.org/W155195423"],"abstract_inverted_index":{"In":[0],"the":[1,3,9,40,52,70,79,85,99,113,121,129],"paper":[2],"construction":[4,64],"of":[5,11,38,59,63,74,87,112,120,131],"test":[6,23,75,101,110,134],"images":[7,76,102,111],"for":[8,15,77],"training":[10,78,132],"convolutional":[12,80,90],"neural":[13,81,91,122],"networks":[14],"image":[16,24,41,135],"contrast":[17,73,86],"automatic":[18],"assessment":[19],"is":[20,26,93],"considered.":[21],"The":[22,116],"database":[25,114],"formed":[27],"by":[28],"using":[29],"a":[30,35,45,56],"random":[31],"number":[32],"generator":[33],"at":[34],"given":[36,46],"coefficient":[37],"filling":[39],"with":[42,44],"pixels":[43,54],"brightness":[47,57],"(from":[48],"0":[49],"to":[50,68,83,95,104],"255),":[51],"remaining":[53],"have":[55],"value":[58],"255.":[60],"This":[61],"method":[62],"makes":[65],"it":[66,97],"possible":[67],"estimate":[69],"global":[71],"absolute":[72],"network":[82,92,123],"assess":[84],"images.":[88],"A":[89],"constructed":[94,100],"train":[96],"on":[98,108],"and":[103,118,133],"verify":[105],"its":[106],"functioning":[107],"real":[109],"TID2013.":[115],"structure":[117],"parameters":[119],"are":[124],"presented,":[125],"as":[126,128],"well":[127],"results":[130],"accuracy.":[136]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}