{"id":"https://openalex.org/W4206713640","doi":"https://doi.org/10.1109/tmc.2021.3133949","title":"QoE Assessment Model Based on Continuous Deep Learning for Video in Wireless Networks","display_name":"QoE Assessment Model Based on Continuous Deep Learning for Video in Wireless Networks","publication_year":2021,"publication_date":"2021-12-09","ids":{"openalex":"https://openalex.org/W4206713640","doi":"https://doi.org/10.1109/tmc.2021.3133949"},"language":"en","primary_location":{"id":"doi:10.1109/tmc.2021.3133949","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmc.2021.3133949","pdf_url":null,"source":{"id":"https://openalex.org/S69141925","display_name":"IEEE Transactions on Mobile Computing","issn_l":"1536-1233","issn":["1536-1233","1558-0660","2161-9875"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Mobile Computing","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/A5115467777","display_name":"Xuewen Liu","orcid":"https://orcid.org/0000-0003-2664-4034"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xuewen Liu","raw_affiliation_strings":["Department of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073849231","display_name":"Gang Chuai","orcid":"https://orcid.org/0000-0002-2261-4551"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Gang Chuai","raw_affiliation_strings":["Department of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100327844","display_name":"Xin Wang","orcid":"https://orcid.org/0000-0001-8639-3818"},"institutions":[{"id":"https://openalex.org/I1327163397","display_name":"State University of New York","ror":"https://ror.org/01q1z8k08","country_code":"US","type":"education","lineage":["https://openalex.org/I1327163397"]},{"id":"https://openalex.org/I59553526","display_name":"Stony Brook University","ror":"https://ror.org/05qghxh33","country_code":"US","type":"education","lineage":["https://openalex.org/I59553526"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xin Wang","raw_affiliation_strings":["Department of Electrical and Computer Engineering, State University of New York at Stony Brook, Stony Brook, NY, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, State University of New York at Stony Brook, Stony Brook, NY, USA","institution_ids":["https://openalex.org/I59553526","https://openalex.org/I1327163397"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101756701","display_name":"Zhiwei Xu","orcid":"https://orcid.org/0000-0001-7733-8219"},"institutions":[{"id":"https://openalex.org/I1327163397","display_name":"State University of New York","ror":"https://ror.org/01q1z8k08","country_code":"US","type":"education","lineage":["https://openalex.org/I1327163397"]},{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210090176","display_name":"Institute of Computing Technology","ror":"https://ror.org/0090r4d87","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]},{"id":"https://openalex.org/I59553526","display_name":"Stony Brook University","ror":"https://ror.org/05qghxh33","country_code":"US","type":"education","lineage":["https://openalex.org/I59553526"]}],"countries":["CN","US"],"is_corresponding":false,"raw_author_name":"Zhiwei Xu","raw_affiliation_strings":["Institute of Computing, Chinese Academy of Sciences, Beijing, China","Department of Electrical and Computer Engineering, State University of New York at Stony Brook, Stony Brook, NY, USA"],"affiliations":[{"raw_affiliation_string":"Institute of Computing, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210090176","https://openalex.org/I19820366"]},{"raw_affiliation_string":"Department of Electrical and Computer Engineering, State University of New York at Stony Brook, Stony Brook, NY, USA","institution_ids":["https://openalex.org/I59553526","https://openalex.org/I1327163397"]}]},{"author_position":"last","author":{"id":null,"display_name":"Weidong Gao","orcid":"https://orcid.org/0000-0002-9360-4561"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weidong Gao","raw_affiliation_strings":["Department of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5115467777"],"corresponding_institution_ids":["https://openalex.org/I139759216"],"apc_list":null,"apc_paid":null,"fwci":0.4855,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.66645662,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"22","issue":"6","first_page":"3619","last_page":"3633"},"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9952999949455261,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T13731","display_name":"Advanced Computing and Algorithms","score":0.9939000010490417,"subfield":{"id":"https://openalex.org/subfields/3322","display_name":"Urban Studies"},"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":0.8575218915939331},{"id":"https://openalex.org/keywords/quality-of-service","display_name":"Quality of service","score":0.6516501903533936},{"id":"https://openalex.org/keywords/quality-of-experience","display_name":"Quality of experience","score":0.615746259689331},{"id":"https://openalex.org/keywords/wireless-network","display_name":"Wireless network","score":0.4737432897090912},{"id":"https://openalex.org/keywords/wireless","display_name":"Wireless","score":0.4639067053794861},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.44651898741722107},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.44241487979888916},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.42989468574523926},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.42081528902053833},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.42042112350463867},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.40988636016845703},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3298226594924927},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.10117509961128235}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8575218915939331},{"id":"https://openalex.org/C5119721","wikidata":"https://www.wikidata.org/wiki/Q220501","display_name":"Quality of service","level":2,"score":0.6516501903533936},{"id":"https://openalex.org/C2779333187","wikidata":"https://www.wikidata.org/wiki/Q3132648","display_name":"Quality of experience","level":3,"score":0.615746259689331},{"id":"https://openalex.org/C108037233","wikidata":"https://www.wikidata.org/wiki/Q11375","display_name":"Wireless network","level":3,"score":0.4737432897090912},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.4639067053794861},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.44651898741722107},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44241487979888916},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.42989468574523926},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.42081528902053833},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.42042112350463867},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.40988636016845703},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3298226594924927},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.10117509961128235},{"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/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tmc.2021.3133949","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmc.2021.3133949","pdf_url":null,"source":{"id":"https://openalex.org/S69141925","display_name":"IEEE Transactions on Mobile Computing","issn_l":"1536-1233","issn":["1536-1233","1558-0660","2161-9875"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Mobile Computing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G6318157388","display_name":null,"funder_award_id":"ECCS 2030063","funder_id":"https://openalex.org/F4320335353","funder_display_name":"National Science Foundation of Sri Lanka"}],"funders":[{"id":"https://openalex.org/F4320322725","display_name":"China Scholarship Council","ror":"https://ror.org/04atp4p48"},{"id":"https://openalex.org/F4320335353","display_name":"National Science Foundation of Sri Lanka","ror":"https://ror.org/010xaa060"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W1546422157","https://openalex.org/W1970200030","https://openalex.org/W1983871517","https://openalex.org/W2022359415","https://openalex.org/W2030821459","https://openalex.org/W2098663851","https://openalex.org/W2104933073","https://openalex.org/W2132549992","https://openalex.org/W2185105561","https://openalex.org/W2248441886","https://openalex.org/W2501289763","https://openalex.org/W2560647685","https://openalex.org/W2726208348","https://openalex.org/W2735521527","https://openalex.org/W2768646057","https://openalex.org/W2788388592","https://openalex.org/W2808096139","https://openalex.org/W2808567040","https://openalex.org/W2921881548","https://openalex.org/W2953565240","https://openalex.org/W2963540014","https://openalex.org/W2964269625","https://openalex.org/W2964303773","https://openalex.org/W2980765376","https://openalex.org/W3011593776","https://openalex.org/W3012012317","https://openalex.org/W3021931813","https://openalex.org/W3027593020","https://openalex.org/W3032592799","https://openalex.org/W3036360157","https://openalex.org/W3048213795","https://openalex.org/W3099793224","https://openalex.org/W3128665664","https://openalex.org/W4319988532","https://openalex.org/W6675634716","https://openalex.org/W6720711607","https://openalex.org/W6742852309","https://openalex.org/W6759579507","https://openalex.org/W6849896277"],"related_works":["https://openalex.org/W2323516465","https://openalex.org/W4238615239","https://openalex.org/W2063960996","https://openalex.org/W2085045797","https://openalex.org/W1998565590","https://openalex.org/W2170179501","https://openalex.org/W3217474284","https://openalex.org/W2044415708","https://openalex.org/W3133147449","https://openalex.org/W1901143057"],"abstract_inverted_index":{"Quality":[0],"of":[1,22,37,43,48,55,60,72,109,125,217,268,280],"experience":[2],"(QoE)":[3],"is":[4,39,52,157,272],"a":[5,58,143],"vital":[6],"metric":[7],"that":[8,47,242,279],"indicates":[9],"how":[10],"well":[11],"the":[12,28,53,70,83,101,107,123,179,189,210,215,230,247,265],"wireless":[13,153],"network":[14,29,89],"provides":[15,292],"transmission":[16],"services":[17],"to":[18,99,103,233],"users,":[19],"while":[20],"quality":[21],"service":[23],"(QoS)":[24],"help":[25,77],"better":[26],"configure":[27],"parameters":[30],"for":[31,119,182],"higher":[32],"performance.":[33],"The":[34,166,184,238],"evaluation":[35],"time":[36,93,202,298],"QoE":[38,51,80,104,145],"usually":[40],"several":[41,261],"orders":[42],"magnitude":[44],"larger":[45],"than":[46,274,278],"QoS,":[49],"because":[50],"perception":[54],"users":[56],"over":[57],"period":[59,203],"time,":[61],"but":[62],"QoS":[63,84,102],"can":[64,76],"be":[65],"collected":[66],"every":[67],"millisecond.":[68],"Therefore,":[69],"implementation":[71],"QoE/QoS":[73,120],"mapping":[74,121],"model":[75,146,156,245,271],"us":[78],"obtain":[79,100],"by":[81,253],"collecting":[82],"measurements,":[85],"and":[86,129,195,220,299],"perform":[87],"QoE-based":[88],"configurations":[90],"with":[91,134,159,193,204,214,260,284],"smaller":[92],"granularity.":[94],"Many":[95],"studies":[96],"are":[97,175],"made":[98],"mapping,":[105],"including":[106],"use":[108,216],"machine":[110],"learning":[111,151,226],"(ML)":[112],"methods.":[113],"However,":[114],"traditional":[115,281],"ML-based":[116],"regression":[117,127,231],"methods":[118],"face":[122],"challenge":[124],"high":[126],"error":[128,232,251,267],"catastrophic":[130,211],"forgetting":[131,212],"in":[132,152,199,295],"dealing":[133],"continuously":[135],"arriving":[136,206],"data.":[137,207],"In":[138],"this":[139],"paper,":[140],"we":[141],"propose":[142],"novel":[144],"based":[147],"on":[148],"continual":[149],"deep":[150,161],"network.":[154],"This":[155],"formed":[158],"two":[160],"neural":[162],"networks":[163],"(DNNs)":[164],"concatenated.":[165],"first":[167],"DNN":[168,181,186],"classifies":[169],"data":[170],"into":[171,178],"different":[172],"subsets,":[173],"which":[174],"then":[176],"fed":[177],"second":[180,185],"regression.":[183],"dynamically":[187],"form":[188],"corresponding":[190],"subnets,":[191],"each":[192,200],"nodes":[194],"connections":[196],"adaptively":[197],"selected":[198],"new":[201,205],"We":[208],"solve":[209],"problem":[213],"node":[218],"splitting":[219],"hidden":[221],"state":[222],"augmentation.":[223],"Our":[224],"proposed":[225,244,270,290],"framework":[227],"greatly":[228],"reduces":[229,246],"as":[234,236],"low":[235],"0.9314%.":[237],"experimental":[239],"results":[240],"demonstrate":[241],"our":[243,269,289],"root":[248],"mean":[249],"square":[250],"(RMSE)":[252],"<inline-formula><tex-math":[254],"notation=\"LaTeX\">$21":[255],"\\sim":[256],"86$</tex-math></inline-formula>":[257],"times":[258,276],"compared":[259],"existing":[262],"approaches,":[263],"specially,":[264],"testing":[266],"more":[273],"80":[275],"lower":[277],"DNN.":[282],"Compared":[283],"other":[285],"DNN-based":[286],"cascade":[287],"models,":[288],"method":[291],"good":[293],"performance":[294],"both":[296],"training":[297],"RMSE.":[300]},"counts_by_year":[{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-10-10T00:00:00"}