{"id":"https://openalex.org/W3088101544","doi":"https://doi.org/10.2352/issn.2470-1173.2020.11.hvei-130","title":"Predicting Single Observer&amp;#x2019;s Votes from Objective Measures using Neural Networks","display_name":"Predicting Single Observer&amp;#x2019;s Votes from Objective Measures using Neural Networks","publication_year":2020,"publication_date":"2020-01-26","ids":{"openalex":"https://openalex.org/W3088101544","doi":"https://doi.org/10.2352/issn.2470-1173.2020.11.hvei-130","mag":"3088101544"},"language":"en","primary_location":{"id":"doi:10.2352/issn.2470-1173.2020.11.hvei-130","is_oa":false,"landing_page_url":"https://doi.org/10.2352/issn.2470-1173.2020.11.hvei-130","pdf_url":null,"source":{"id":"https://openalex.org/S4210227276","display_name":"Electronic Imaging","issn_l":"2470-1173","issn":["2470-1173"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Electronic Imaging","raw_type":"journal-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/A5033546468","display_name":"Lohic Fotio Tiotsop","orcid":"https://orcid.org/0000-0001-5127-9935"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lohic Fotio Tiotsop","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081939696","display_name":"Tomas Mizdos","orcid":"https://orcid.org/0000-0001-7158-7660"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tomas Mizdos","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008811787","display_name":"Miroslav Uhrina","orcid":"https://orcid.org/0000-0002-5983-6019"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Miroslav Uhrina","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088206114","display_name":"Peter Po\u010dta","orcid":"https://orcid.org/0000-0001-6791-1325"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Peter Pocta","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006111389","display_name":"Marcus Barkowsky","orcid":"https://orcid.org/0000-0003-2739-3708"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Marcus Barkowsky","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5052707121","display_name":"Enrico Masala","orcid":"https://orcid.org/0000-0001-8906-354X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Enrico Masala","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.1354,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.56294624,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":"32","issue":"11","first_page":"130","last_page":"1"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.945900022983551,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10320","display_name":"Neural Networks and Applications","score":0.945900022983551,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T11165","display_name":"Image and Video Quality Assessment","score":0.9327999949455261,"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/T12611","display_name":"Neural Networks and Reservoir Computing","score":0.9225999712944031,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/artificial-neural-network","display_name":"Artificial neural network","score":0.6265183687210083},{"id":"https://openalex.org/keywords/observer","display_name":"Observer (physics)","score":0.5060643553733826},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.44740086793899536},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.44314831495285034},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.3795710802078247},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.35933101177215576},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.055741339921951294}],"concepts":[{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6265183687210083},{"id":"https://openalex.org/C2780704645","wikidata":"https://www.wikidata.org/wiki/Q9251458","display_name":"Observer (physics)","level":2,"score":0.5060643553733826},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.44740086793899536},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44314831495285034},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.3795710802078247},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.35933101177215576},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.055741339921951294},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.2352/issn.2470-1173.2020.11.hvei-130","is_oa":false,"landing_page_url":"https://doi.org/10.2352/issn.2470-1173.2020.11.hvei-130","pdf_url":null,"source":{"id":"https://openalex.org/S4210227276","display_name":"Electronic Imaging","issn_l":"2470-1173","issn":["2470-1173"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Electronic Imaging","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W4286629047","https://openalex.org/W3046775127","https://openalex.org/W3107602296","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W4313488044","https://openalex.org/W3209574120","https://openalex.org/W4312192474"],"abstract_inverted_index":{"The":[0],"last":[1],"decades":[2],"witnessed":[3],"an":[4,20,103],"increasing":[5],"number":[6,157],"of":[7,22,28,38,58,78,139,158,169,184],"works":[8],"aiming":[9],"at":[10,95],"proposing":[11],"objective":[12],"measures":[13],"for":[14,86,164],"media":[15],"quality":[16,80,138,143],"assessment,":[17],"i.e.":[18],"determining":[19],"estimation":[21],"the":[23,48,56,112,115,135,152,166,170,185],"mean":[24],"opinion":[25,44],"score":[26,113],"(MOS)":[27],"human":[29],"observers.":[30],"In":[31],"this":[32],"contribution,":[33],"we":[34,52],"investigate":[35],"a":[36,64,107,140,156,182],"possibility":[37],"modeling":[39],"and":[40,109,147],"predicting":[41],"single":[42,60],"observer\u2019s":[43],"scores":[45],"rather":[46],"than":[47],"MOS.":[49],"More":[50],"precisely,":[51],"attempt":[53],"to":[54,71,129,177],"approximate":[55],"choice":[57],"one":[59],"observer":[61,74,117],"by":[62],"designing":[63],"neural":[65],"network":[66],"(NN)":[67],"that":[68,73,114,123],"is":[69,144],"expected":[70],"mimic":[72],"behavior":[75],"in":[76],"terms":[77],"visual":[79,137],"perception.":[81],"Once":[82],"such":[83,162],"NNs":[84],"(one":[85],"each":[87],"observer)":[88],"are":[89,175],"trained":[90],"they":[91,100,110],"can":[92],"be":[93],"looked":[94],"as":[96,99,102],"\u201cvirtual":[97],"observers\u201d":[98],"take":[101],"input":[104],"information":[105],"about":[106],"sequence":[108,141],"output":[111],"related":[116],"would":[118],"have":[119],"given":[120],"after":[121],"watching":[122],"sequence.":[124],"This":[125],"new":[126],"approach":[127],"allows":[128],"automatically":[130],"get":[131],"different":[132],"opinions":[133],"regarding":[134],"perceived":[136],"whose":[142],"under":[145],"investigation":[146],"thus":[148],"estimate":[149],"not":[150],"only":[151],"MOS":[153],"but":[154],"also":[155],"other":[159],"statistical":[160],"indexes":[161],"as,":[163],"instance,":[165],"standard":[167],"deviation":[168],"opinions.":[171],"Large":[172],"numerical":[173],"experiments":[174],"performed":[176],"provide":[178],"further":[179],"insight":[180],"into":[181],"suitability":[183],"approach.":[186]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2020-10-01T00:00:00"}
