{"id":"https://openalex.org/W2967457832","doi":"https://doi.org/10.1109/eucnc.2019.8801974","title":"Application of Deep Learning Techniques to Video QoE Prediction in Smartphones","display_name":"Application of Deep Learning Techniques to Video QoE Prediction in Smartphones","publication_year":2019,"publication_date":"2019-06-01","ids":{"openalex":"https://openalex.org/W2967457832","doi":"https://doi.org/10.1109/eucnc.2019.8801974","mag":"2967457832"},"language":"en","primary_location":{"id":"doi:10.1109/eucnc.2019.8801974","is_oa":false,"landing_page_url":"https://doi.org/10.1109/eucnc.2019.8801974","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 European Conference on Networks and Communications (EuCNC)","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/A5085248488","display_name":"Carlos Cardenas-Angelat","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Carlos Cardenas-Angelat","raw_affiliation_strings":["DEKRA Testing and Certification S.A.U., M\u00e1laga, Spain"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"DEKRA Testing and Certification S.A.U., M\u00e1laga, Spain","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073427316","display_name":"Janie Banos Polglase","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Janie Banos Polglase","raw_affiliation_strings":["DEKRA Testing and Certification S.A.U., M\u00e1laga, Spain"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"DEKRA Testing and Certification S.A.U., M\u00e1laga, Spain","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022825651","display_name":"Cristian J. Vaca-Rubio","orcid":"https://orcid.org/0000-0002-9713-2784"},"institutions":[{"id":"https://openalex.org/I82767444","display_name":"Universidad de M\u00e1laga","ror":"https://ror.org/036b2ww28","country_code":"ES","type":"education","lineage":["https://openalex.org/I82767444"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Cristian J. Vaca-Rubio","raw_affiliation_strings":["Universidad de M\u00e1laga, M\u00e1laga, Spain"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universidad de M\u00e1laga, M\u00e1laga, Spain","institution_ids":["https://openalex.org/I82767444"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5064111002","display_name":"Mari Carmen Aguayo\u2010Torres","orcid":"https://orcid.org/0000-0002-3572-4354"},"institutions":[{"id":"https://openalex.org/I82767444","display_name":"Universidad de M\u00e1laga","ror":"https://ror.org/036b2ww28","country_code":"ES","type":"education","lineage":["https://openalex.org/I82767444"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Mari Carmen Aguayo-Torres","raw_affiliation_strings":["Universidad de M\u00e1laga, M\u00e1laga, Spain"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universidad de M\u00e1laga, M\u00e1laga, Spain","institution_ids":["https://openalex.org/I82767444"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.2034,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.53875951,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"abs 1707 8114","issue":null,"first_page":"252","last_page":"256"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11165","display_name":"Image and Video Quality Assessment","score":0.9998999834060669,"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/T11165","display_name":"Image and Video Quality Assessment","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/T10901","display_name":"Advanced Data Compression Techniques","score":0.9915000200271606,"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/T12720","display_name":"Multimedia Communication and Technology","score":0.9781000018119812,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8010845184326172},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5877640247344971},{"id":"https://openalex.org/keywords/video-streaming","display_name":"Video streaming","score":0.5046769380569458},{"id":"https://openalex.org/keywords/multimedia","display_name":"Multimedia","score":0.48058271408081055},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4016053080558777},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.33583736419677734},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3298262655735016},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.32698357105255127}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8010845184326172},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5877640247344971},{"id":"https://openalex.org/C2986160907","wikidata":"https://www.wikidata.org/wiki/Q220499","display_name":"Video streaming","level":2,"score":0.5046769380569458},{"id":"https://openalex.org/C49774154","wikidata":"https://www.wikidata.org/wiki/Q131765","display_name":"Multimedia","level":1,"score":0.48058271408081055},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4016053080558777},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.33583736419677734},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3298262655735016},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.32698357105255127}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/eucnc.2019.8801974","is_oa":false,"landing_page_url":"https://doi.org/10.1109/eucnc.2019.8801974","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 European Conference on Networks and Communications (EuCNC)","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":18,"referenced_works":["https://openalex.org/W1487333565","https://openalex.org/W1510438915","https://openalex.org/W1665214252","https://openalex.org/W2095705004","https://openalex.org/W2107330855","https://openalex.org/W2120375663","https://openalex.org/W2163605009","https://openalex.org/W2604764451","https://openalex.org/W2610855322","https://openalex.org/W2740604066","https://openalex.org/W2742079690","https://openalex.org/W2911961045","https://openalex.org/W4236362309","https://openalex.org/W6637242042","https://openalex.org/W6674330103","https://openalex.org/W6684191040","https://openalex.org/W6742058293","https://openalex.org/W6758677370"],"related_works":["https://openalex.org/W4375867731","https://openalex.org/W2611989081","https://openalex.org/W4230611425","https://openalex.org/W2731899572","https://openalex.org/W4304166257","https://openalex.org/W4294635752","https://openalex.org/W4383066092","https://openalex.org/W3215138031","https://openalex.org/W3162258837","https://openalex.org/W2121543627"],"abstract_inverted_index":{"This":[0],"paper":[1],"evaluates":[2],"the":[3,12,28,64,73,83,92,97,101,135,146,160],"use":[4],"of":[5,14,16,50,69,85,103,148],"deep":[6,33],"learning":[7,94],"prediction":[8,65],"models":[9,57,113],"for":[10,32,63],"assessing":[11],"quality":[13],"experience":[15],"video":[17],"applications":[18,120],"using":[19],"input":[20,90],"data":[21,70,105],"from":[22,82],"a":[23,75,141],"single":[24,36],"measuring":[25],"point":[26],"at":[27,155],"smartphone.":[29],"Three":[30],"architectures":[31],"neural":[34,99],"networks,":[35],"task":[37],"fully":[38,161],"connected":[39],"(FC),":[40],"multitask":[41],"FC":[42],"and":[43],"convolutional,":[44],"have":[45,114],"been":[46,59,115],"implemented.":[47],"A":[48],"set":[49,137],"four":[51],"relevant":[52],"metrics":[53],"recommended":[54],"by":[55,72],"ITU-T":[56],"has":[58],"considered":[60],"as":[61,89,109,145],"outputs":[62],"models.":[66],"The":[67,111,130],"amount":[68,102],"received":[71],"device,":[74],"parameter":[76],"which":[77],"can":[78],"be":[79,125],"easily":[80],"extracted":[81],"majority":[84],"smartphones,":[86,122],"is":[87,106,138,152],"used":[88,108],"to":[91,117,127,159],"machine":[93],"algorithms.":[95],"For":[96],"convolutional":[98],"model,":[100],"transmitted":[104],"also":[107],"input.":[110],"predictions":[112],"applied":[116],"evaluate":[118],"YouTube":[119],"on":[121,134],"but":[123],"could":[124],"generalized":[126],"other":[128],"services.":[129],"overall":[131],"achieved":[132],"performance":[133],"test":[136,163],"around":[139],"90%,":[140],"very":[142],"promising":[143],"result":[144],"generation":[147],"new":[149],"labelled":[150],"datasets":[151],"quite":[153],"feasible":[154],"low":[156],"cost":[157],"thanks":[158],"automated":[162],"setup":[164],"developed.":[165]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}