{"id":"https://openalex.org/W3092058246","doi":"https://doi.org/10.2352/issn.2470-1173.2020.9.iqsp-168","title":"No Reference Video Quality Assessment with authentic distortions using 3-D Deep Convolutional Neural Network","display_name":"No Reference Video Quality Assessment with authentic distortions using 3-D Deep Convolutional Neural Network","publication_year":2020,"publication_date":"2020-01-11","ids":{"openalex":"https://openalex.org/W3092058246","doi":"https://doi.org/10.2352/issn.2470-1173.2020.9.iqsp-168","mag":"3092058246"},"language":"en","primary_location":{"id":"doi:10.2352/issn.2470-1173.2020.9.iqsp-168","is_oa":false,"landing_page_url":"https://doi.org/10.2352/issn.2470-1173.2020.9.iqsp-168","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/A5041267792","display_name":"Roger Gomez Nieto","orcid":"https://orcid.org/0000-0003-4390-6251"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Roger Gomez Nieto","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008167952","display_name":"Hern\u00e1n Dar\u00edo Ben\u00edtez Restrepo","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hernan Dario Benitez Restrepo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050009440","display_name":"Roger Figueroa Quintero","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Roger Figueroa Quintero","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5075463806","display_name":"Alan C. Bovik","orcid":"https://orcid.org/0000-0001-6067-710X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Alan Bovik","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0979,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.41454576,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"32","issue":"9","first_page":"168","last_page":"1"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11165","display_name":"Image and Video Quality Assessment","score":0.9997000098228455,"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/T11165","display_name":"Image and Video Quality Assessment","score":0.9997000098228455,"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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9914000034332275,"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/T11605","display_name":"Visual Attention and Saliency Detection","score":0.98580002784729,"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":0.8093763589859009},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7844606637954712},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7535231113433838},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6351455450057983},{"id":"https://openalex.org/keywords/video-quality","display_name":"Video quality","score":0.5758819580078125},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.48992985486984253},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4683149755001068},{"id":"https://openalex.org/keywords/quality-score","display_name":"Quality Score","score":0.4615045189857483},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.44296425580978394},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.43299853801727295},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.4211544692516327},{"id":"https://openalex.org/keywords/mean-opinion-score","display_name":"Mean opinion score","score":0.4112228751182556},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.382254958152771},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3285279870033264}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8093763589859009},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7844606637954712},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7535231113433838},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6351455450057983},{"id":"https://openalex.org/C103910844","wikidata":"https://www.wikidata.org/wiki/Q2631256","display_name":"Video quality","level":3,"score":0.5758819580078125},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.48992985486984253},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4683149755001068},{"id":"https://openalex.org/C2779346075","wikidata":"https://www.wikidata.org/wiki/Q7268763","display_name":"Quality Score","level":3,"score":0.4615045189857483},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.44296425580978394},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.43299853801727295},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.4211544692516327},{"id":"https://openalex.org/C62897895","wikidata":"https://www.wikidata.org/wiki/Q1915482","display_name":"Mean opinion score","level":3,"score":0.4112228751182556},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.382254958152771},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3285279870033264},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.2352/issn.2470-1173.2020.9.iqsp-168","is_oa":false,"landing_page_url":"https://doi.org/10.2352/issn.2470-1173.2020.9.iqsp-168","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":[{"display_name":"Reduced inequalities","score":0.6600000262260437,"id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2046455617","https://openalex.org/W1995358030","https://openalex.org/W2611572988","https://openalex.org/W2100602544","https://openalex.org/W1997117005","https://openalex.org/W2795889627","https://openalex.org/W2943685190","https://openalex.org/W3027116454","https://openalex.org/W4281615817","https://openalex.org/W2802214191"],"abstract_inverted_index":{"Video":[0],"Quality":[1],"Assessment":[2],"(VQA)":[3],"is":[4,31],"an":[5],"essential":[6],"topic":[7],"in":[8,102],"several":[9,82],"industries":[10],"ranging":[11],"from":[12,81],"video":[13,131],"streaming":[14],"to":[15,59,68,72,92],"camera":[16],"manufacturing.":[17],"In":[18],"this":[19],"paper,":[20],"we":[21],"present":[22],"a":[23,61],"novel":[24],"method":[25],"for":[26],"No-Reference":[27],"VQA.":[28],"This":[29],"framework":[30],"fast":[32],"and":[33,52,85,124],"does":[34],"not":[35],"require":[36],"the":[37,89,94,99,108],"extraction":[38],"of":[39,46,118],"hand-crafted":[40],"features.":[41,77],"We":[42,64,78,97,105],"extracted":[43,79],"convolutional":[44],"features":[45,80],"3-D":[47],"C3D":[48],"Convolutional":[49],"Neural":[50],"Network":[51],"feed":[53],"one":[54,114],"trained":[55],"Support":[56],"Vector":[57],"Regressor":[58],"obtain":[60],"VQA":[62,95,137],"score.":[63,96],"did":[65],"certain":[66],"transformations":[67],"different":[69],"color":[70],"spaces":[71],"generate":[73],"better":[74],"discriminant":[75],"deep":[76],"layers,":[83],"with":[84,120],"without":[86],"overlap,":[87],"finding":[88],"best":[90],"configuration":[91],"improve":[93],"tested":[98],"proposed":[100],"approach":[101],"LIVE-Qualcomm":[103],"dataset.":[104],"extensively":[106],"evaluated":[107],"perceptual":[109],"quality":[110,132],"prediction":[111],"model,":[112],"obtaining":[113],"final":[115],"Pearson":[116],"correlation":[117],"0:7749±0:0884":[119],"Mean":[121],"Opinion":[122],"Scores,":[123],"showed":[125],"that":[126],"it":[127],"can":[128],"achieve":[129],"good":[130],"prediction,":[133],"outperforming":[134],"other":[135],"state-of-the-art":[136],"leading":[138],"models.":[139]},"counts_by_year":[{"year":2021,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}