{"id":"https://openalex.org/W4312966191","doi":"https://doi.org/10.1109/mmsp55362.2022.9948927","title":"GreenBIQA: A Lightweight Blind Image Quality Assessment Method","display_name":"GreenBIQA: A Lightweight Blind Image Quality Assessment Method","publication_year":2022,"publication_date":"2022-09-26","ids":{"openalex":"https://openalex.org/W4312966191","doi":"https://doi.org/10.1109/mmsp55362.2022.9948927"},"language":"en","primary_location":{"id":"doi:10.1109/mmsp55362.2022.9948927","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mmsp55362.2022.9948927","pdf_url":null,"source":{"id":"https://openalex.org/S4363605768","display_name":"2022 IEEE 24th International Workshop on Multimedia Signal Processing (MMSP)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE 24th International Workshop on Multimedia Signal Processing (MMSP)","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/A5024738575","display_name":"Zhanxuan Mei","orcid":"https://orcid.org/0009-0008-8049-6822"},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Zhanxuan Mei","raw_affiliation_strings":["University of Southern California,Los Angeles,California,USA","University of Southern California, Los Angeles, California, USA"],"affiliations":[{"raw_affiliation_string":"University of Southern California,Los Angeles,California,USA","institution_ids":["https://openalex.org/I1174212"]},{"raw_affiliation_string":"University of Southern California, Los Angeles, California, USA","institution_ids":["https://openalex.org/I1174212"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102766141","display_name":"Yun-Cheng Wang","orcid":"https://orcid.org/0000-0001-9778-4806"},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yun-Cheng Wang","raw_affiliation_strings":["University of Southern California,Los Angeles,California,USA","University of Southern California, Los Angeles, California, USA"],"affiliations":[{"raw_affiliation_string":"University of Southern California,Los Angeles,California,USA","institution_ids":["https://openalex.org/I1174212"]},{"raw_affiliation_string":"University of Southern California, Los Angeles, California, USA","institution_ids":["https://openalex.org/I1174212"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079819809","display_name":"Xingze He","orcid":null},"institutions":[{"id":"https://openalex.org/I4210099336","display_name":"Menlo School","ror":"https://ror.org/01240pn49","country_code":"US","type":"education","lineage":["https://openalex.org/I4210099336"]},{"id":"https://openalex.org/I4210114444","display_name":"Meta (United States)","ror":"https://ror.org/01zbnvs85","country_code":"US","type":"company","lineage":["https://openalex.org/I4210114444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xingze He","raw_affiliation_strings":["Meta Platform, Inc.,Menlo Park,California,USA","Meta Platform, Inc., Menlo Park, California, USA"],"affiliations":[{"raw_affiliation_string":"Meta Platform, Inc.,Menlo Park,California,USA","institution_ids":["https://openalex.org/I4210114444"]},{"raw_affiliation_string":"Meta Platform, Inc., Menlo Park, California, USA","institution_ids":["https://openalex.org/I4210114444","https://openalex.org/I4210099336"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5001082656","display_name":"C.\u2010C. Jay Kuo","orcid":"https://orcid.org/0000-0001-9474-5035"},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"C.-C. Jay Kuo","raw_affiliation_strings":["University of Southern California,Los Angeles,California,USA","University of Southern California, Los Angeles, California, USA"],"affiliations":[{"raw_affiliation_string":"University of Southern California,Los Angeles,California,USA","institution_ids":["https://openalex.org/I1174212"]},{"raw_affiliation_string":"University of Southern California, Los Angeles, California, USA","institution_ids":["https://openalex.org/I1174212"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5024738575"],"corresponding_institution_ids":["https://openalex.org/I1174212"],"apc_list":null,"apc_paid":null,"fwci":0.7164,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.7979418,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"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/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9952999949455261,"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/T11019","display_name":"Image Enhancement Techniques","score":0.9941999912261963,"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":0.8447763919830322},{"id":"https://openalex.org/keywords/distortion","display_name":"Distortion (music)","score":0.7135826945304871},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6072815656661987},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.5792878866195679},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5597140789031982},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5128265023231506},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.5126780271530151},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.5031999945640564},{"id":"https://openalex.org/keywords/image-quality","display_name":"Image quality","score":0.48837941884994507},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.48052796721458435},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.47798389196395874},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4728280007839203},{"id":"https://openalex.org/keywords/source-code","display_name":"Source code","score":0.44909438490867615},{"id":"https://openalex.org/keywords/computational-complexity-theory","display_name":"Computational complexity theory","score":0.4240877330303192},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.41880300641059875},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3798561096191406},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.16438409686088562},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.15370801091194153}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8447763919830322},{"id":"https://openalex.org/C126780896","wikidata":"https://www.wikidata.org/wiki/Q899871","display_name":"Distortion (music)","level":4,"score":0.7135826945304871},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6072815656661987},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.5792878866195679},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5597140789031982},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5128265023231506},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.5126780271530151},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.5031999945640564},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.48837941884994507},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.48052796721458435},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.47798389196395874},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4728280007839203},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.44909438490867615},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.4240877330303192},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.41880300641059875},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3798561096191406},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.16438409686088562},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.15370801091194153},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","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/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C2776257435","wikidata":"https://www.wikidata.org/wiki/Q1576430","display_name":"Bandwidth (computing)","level":2,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C194257627","wikidata":"https://www.wikidata.org/wiki/Q211554","display_name":"Amplifier","level":3,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/mmsp55362.2022.9948927","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mmsp55362.2022.9948927","pdf_url":null,"source":{"id":"https://openalex.org/S4363605768","display_name":"2022 IEEE 24th International Workshop on Multimedia Signal Processing (MMSP)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE 24th International Workshop on Multimedia Signal Processing (MMSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9","score":0.4099999964237213}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W1973175507","https://openalex.org/W1982471090","https://openalex.org/W1987489060","https://openalex.org/W2051596736","https://openalex.org/W2102166818","https://openalex.org/W2108598243","https://openalex.org/W2129644086","https://openalex.org/W2133665775","https://openalex.org/W2141983208","https://openalex.org/W2148848374","https://openalex.org/W2171349048","https://openalex.org/W2270330859","https://openalex.org/W2295598076","https://openalex.org/W2473697052","https://openalex.org/W2563786098","https://openalex.org/W2566149141","https://openalex.org/W2891645170","https://openalex.org/W2894843516","https://openalex.org/W2905544033","https://openalex.org/W2953590133","https://openalex.org/W2971622202","https://openalex.org/W3002992380","https://openalex.org/W3035719652","https://openalex.org/W3091249416","https://openalex.org/W3100404621","https://openalex.org/W4313148451","https://openalex.org/W6647225686"],"related_works":["https://openalex.org/W2328889547","https://openalex.org/W2380784125","https://openalex.org/W3003858543","https://openalex.org/W1969547578","https://openalex.org/W3004057759","https://openalex.org/W4312306082","https://openalex.org/W2889085215","https://openalex.org/W2914806737","https://openalex.org/W2998216295","https://openalex.org/W2378029901"],"abstract_inverted_index":{"Deep":[0],"neural":[1],"networks":[2],"(DNNs)":[3],"achieve":[4],"great":[5],"success":[6],"in":[7,17,114],"blind":[8],"image":[9],"quality":[10,86],"assessment":[11],"(BIQA)":[12],"with":[13,119],"large":[14],"pre-trained":[15],"models":[16],"recent":[18],"years.":[19],"Their":[20],"solutions":[21],"cannot":[22],"be":[23],"easily":[24],"deployed":[25],"at":[26,50],"mobile":[27],"or":[28],"edge":[29],"devices,":[30],"and":[31,56,68,103,122],"a":[32,42,57,69],"lightweight":[33],"solution":[34],"is":[35,112,127],"desired.":[36],"In":[37],"this":[38],"work,":[39],"we":[40],"propose":[41],"novel":[43],"BIQA":[44],"model,":[45],"called":[46],"GreenBIQA,":[47],"that":[48,110],"aims":[49],"high":[51],"performance,":[52],"low":[53],"computational":[54],"complexity":[55,121],"small":[58],"model":[59,124],"size.":[60],"GreenBIQA":[61,111],"adopts":[62],"an":[63,81],"unsupervised":[64],"feature":[65,71],"generation":[66],"method":[67,73],"supervised":[70],"selection":[72],"to":[74,84],"extract":[75],"quality-aware":[76],"features.":[77],"Then,":[78],"it":[79],"trains":[80],"XGBoost":[82],"regressor":[83],"predict":[85],"scores":[87],"of":[88],"test":[89],"images.":[90],"We":[91],"conduct":[92],"experiments":[93],"on":[94],"four":[95],"popular":[96],"IQA":[97],"datasets,":[98],"which":[99],"include":[100],"two":[101,104],"synthetic-distortion":[102],"authentic-distortion":[105],"datasets.":[106],"Experimental":[107],"results":[108],"show":[109],"competitive":[113],"performance":[115],"against":[116],"state-of-the-art":[117],"DNNs":[118],"lower":[120],"smaller":[123],"sizes.":[125],"Code":[126],"available":[128],"at:":[129],"https://github.com/zhanxuanm/GreenBIQA":[130]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":1}],"updated_date":"2026-04-02T15:55:50.835912","created_date":"2025-10-10T00:00:00"}