{"id":"https://openalex.org/W7143279092","doi":"https://doi.org/10.1111/cgf.70369","title":"ML\u2010PEA: Machine Learning\u2010Based Perceptual Algorithms for Display Power Optimization","display_name":"ML\u2010PEA: Machine Learning\u2010Based Perceptual Algorithms for Display Power Optimization","publication_year":2026,"publication_date":"2026-03-30","ids":{"openalex":"https://openalex.org/W7143279092","doi":"https://doi.org/10.1111/cgf.70369"},"language":"en","primary_location":{"id":"doi:10.1111/cgf.70369","is_oa":false,"landing_page_url":"https://doi.org/10.1111/cgf.70369","pdf_url":null,"source":{"id":"https://openalex.org/S67831204","display_name":"Computer Graphics Forum","issn_l":"0167-7055","issn":["0167-7055","1467-8659"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320595","host_organization_name":"Wiley","host_organization_lineage":["https://openalex.org/P4310320595"],"host_organization_lineage_names":["Wiley"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computer Graphics Forum","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/A5031004506","display_name":"K. K. Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I57206974","display_name":"New York University","ror":"https://ror.org/0190ak572","country_code":"US","type":"education","lineage":["https://openalex.org/I57206974"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kenneth Chen","raw_affiliation_strings":["New York University  USA"],"raw_orcid":"https://orcid.org/0000-0002-8095-4407","affiliations":[{"raw_affiliation_string":"New York University  USA","institution_ids":["https://openalex.org/I57206974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030844535","display_name":"Nathan Matsuda","orcid":"https://orcid.org/0009-0003-0697-7672"},"institutions":[{"id":"https://openalex.org/I4210128585","display_name":"META Health","ror":"https://ror.org/035h67p10","country_code":"US","type":"other","lineage":["https://openalex.org/I4210128585"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nathan Matsuda","raw_affiliation_strings":["Meta Reality Labs  USA"],"raw_orcid":"https://orcid.org/0009-0003-0697-7672","affiliations":[{"raw_affiliation_string":"Meta Reality Labs  USA","institution_ids":["https://openalex.org/I4210128585"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086548717","display_name":"Thomas Wan","orcid":"https://orcid.org/0009-0006-4320-7548"},"institutions":[{"id":"https://openalex.org/I4210128585","display_name":"META Health","ror":"https://ror.org/035h67p10","country_code":"US","type":"other","lineage":["https://openalex.org/I4210128585"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Thomas Wan","raw_affiliation_strings":["Meta Reality Labs  USA"],"raw_orcid":"https://orcid.org/0009-0006-4320-7548","affiliations":[{"raw_affiliation_string":"Meta Reality Labs  USA","institution_ids":["https://openalex.org/I4210128585"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074061072","display_name":"Ajit Ninan","orcid":"https://orcid.org/0000-0002-6962-1687"},"institutions":[{"id":"https://openalex.org/I4210128585","display_name":"META Health","ror":"https://ror.org/035h67p10","country_code":"US","type":"other","lineage":["https://openalex.org/I4210128585"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ajit Ninan","raw_affiliation_strings":["Meta Reality Labs  USA"],"raw_orcid":"https://orcid.org/0000-0002-6962-1687","affiliations":[{"raw_affiliation_string":"Meta Reality Labs  USA","institution_ids":["https://openalex.org/I4210128585"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077276484","display_name":"Alexandre Chapiro","orcid":"https://orcid.org/0000-0002-7367-0131"},"institutions":[{"id":"https://openalex.org/I4210128585","display_name":"META Health","ror":"https://ror.org/035h67p10","country_code":"US","type":"other","lineage":["https://openalex.org/I4210128585"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Alexandre Chapiro","raw_affiliation_strings":["Meta Reality Labs  USA"],"raw_orcid":"https://orcid.org/0000-0002-7367-0131","affiliations":[{"raw_affiliation_string":"Meta Reality Labs  USA","institution_ids":["https://openalex.org/I4210128585"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5025243341","display_name":"Qi Sun","orcid":"https://orcid.org/0000-0002-3094-5844"},"institutions":[{"id":"https://openalex.org/I57206974","display_name":"New York University","ror":"https://ror.org/0190ak572","country_code":"US","type":"education","lineage":["https://openalex.org/I57206974"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Qi Sun","raw_affiliation_strings":["New York University  USA"],"raw_orcid":"https://orcid.org/0000-0002-3094-5844","affiliations":[{"raw_affiliation_string":"New York University  USA","institution_ids":["https://openalex.org/I57206974"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":3710,"currency":"USD","value_usd":3710},"apc_paid":null,"fwci":3.2056,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.91169613,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12238","display_name":"Green IT and Sustainability","score":0.48489999771118164,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12238","display_name":"Green IT and Sustainability","score":0.48489999771118164,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"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/T10789","display_name":"Interactive and Immersive Displays","score":0.042399998754262924,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"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/T10121","display_name":"Building Energy and Comfort Optimization","score":0.023000000044703484,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.7009000182151794},{"id":"https://openalex.org/keywords/heuristics","display_name":"Heuristics","score":0.550599992275238},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.5009999871253967},{"id":"https://openalex.org/keywords/image-quality","display_name":"Image quality","score":0.43209999799728394},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.42570000886917114},{"id":"https://openalex.org/keywords/power","display_name":"Power (physics)","score":0.42149999737739563},{"id":"https://openalex.org/keywords/perception","display_name":"Perception","score":0.4074000120162964},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.35580000281333923},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.33480000495910645}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7829999923706055},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.7009000182151794},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5819000005722046},{"id":"https://openalex.org/C127705205","wikidata":"https://www.wikidata.org/wiki/Q5748245","display_name":"Heuristics","level":2,"score":0.550599992275238},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.5009999871253967},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.49619999527931213},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.43209999799728394},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.42570000886917114},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.42149999737739563},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.4074000120162964},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.35580000281333923},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.33480000495910645},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3312000036239624},{"id":"https://openalex.org/C194969405","wikidata":"https://www.wikidata.org/wiki/Q170519","display_name":"Virtual reality","level":2,"score":0.30970001220703125},{"id":"https://openalex.org/C2984118289","wikidata":"https://www.wikidata.org/wiki/Q29954","display_name":"Power consumption","level":3,"score":0.30730000138282776},{"id":"https://openalex.org/C173552908","wikidata":"https://www.wikidata.org/wiki/Q1366289","display_name":"Graphics pipeline","level":4,"score":0.3070000112056732},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.3009999990463257},{"id":"https://openalex.org/C164597639","wikidata":"https://www.wikidata.org/wiki/Q327065","display_name":"Display device","level":2,"score":0.2824999988079071},{"id":"https://openalex.org/C160086991","wikidata":"https://www.wikidata.org/wiki/Q5939193","display_name":"Human visual system model","level":3,"score":0.27410000562667847},{"id":"https://openalex.org/C121684516","wikidata":"https://www.wikidata.org/wiki/Q7600677","display_name":"Computer graphics (images)","level":1,"score":0.27250000834465027},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.27059999108314514},{"id":"https://openalex.org/C1223959","wikidata":"https://www.wikidata.org/wiki/Q1191960","display_name":"Stereo display","level":2,"score":0.26489999890327454},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.26330000162124634},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.2630000114440918},{"id":"https://openalex.org/C2779903281","wikidata":"https://www.wikidata.org/wiki/Q6888026","display_name":"Modalities","level":2,"score":0.2612000107765198},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.2581999897956848},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.257999986410141},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.25279998779296875}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1111/cgf.70369","is_oa":false,"landing_page_url":"https://doi.org/10.1111/cgf.70369","pdf_url":null,"source":{"id":"https://openalex.org/S67831204","display_name":"Computer Graphics Forum","issn_l":"0167-7055","issn":["0167-7055","1467-8659"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320595","host_organization_name":"Wiley","host_organization_lineage":["https://openalex.org/P4310320595"],"host_organization_lineage_names":["Wiley"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computer Graphics Forum","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Affordable and clean energy","score":0.8086046576499939,"id":"https://metadata.un.org/sdg/7"}],"awards":[{"id":"https://openalex.org/G1532742376","display_name":"Collaborative Research: CNS Core: HCC: Small: Enabling Efficient Computer Systems for Augmented and Virtual Reality: A Perception-Guided Approach","funder_award_id":"2225861","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":37,"referenced_works":["https://openalex.org/W1580389772","https://openalex.org/W1901129140","https://openalex.org/W1965638809","https://openalex.org/W1982471090","https://openalex.org/W1987931295","https://openalex.org/W2004362396","https://openalex.org/W2017279664","https://openalex.org/W2061501622","https://openalex.org/W2084267193","https://openalex.org/W2115661474","https://openalex.org/W2123185187","https://openalex.org/W2133665775","https://openalex.org/W2139284571","https://openalex.org/W2141204096","https://openalex.org/W2308809577","https://openalex.org/W2331128040","https://openalex.org/W2481798478","https://openalex.org/W2513500606","https://openalex.org/W2604969152","https://openalex.org/W2741137940","https://openalex.org/W2786023220","https://openalex.org/W2889822253","https://openalex.org/W2983810994","https://openalex.org/W3080556461","https://openalex.org/W3103002100","https://openalex.org/W3168989576","https://openalex.org/W4223986629","https://openalex.org/W4243318597","https://openalex.org/W4385320745","https://openalex.org/W4386596862","https://openalex.org/W4387129616","https://openalex.org/W4393245428","https://openalex.org/W4400819459","https://openalex.org/W4400822490","https://openalex.org/W4403941309","https://openalex.org/W4412595425","https://openalex.org/W6945350440"],"related_works":[],"abstract_inverted_index":{"Abstract":[0],"Image":[1],"processing":[2],"techniques":[3,89],"can":[4,221],"be":[5,222],"used":[6,121],"to":[7,15,40,122,127,212],"modulate":[8,123],"the":[9,17,21,33,42],"pixel":[10],"intensities":[11],"of":[12,20,27,30,166,209],"an":[13],"image":[14,45,140],"reduce":[16],"power":[18,49,107,175,193,214],"consumption":[19],"display":[22,69,87,174,213],"device.":[23],"A":[24],"simple":[25],"example":[26],"this":[28,79],"consists":[29],"uniformly":[31],"dimming":[32,115,118,188],"entire":[34],"image.":[35,131],"Such":[36],"algorithms":[37],"should":[38],"strive":[39],"minimize":[41],"impact":[43],"on":[44,53,83,172],"quality":[46,141],"while":[47],"maximizing":[48],"savings.":[50],"Techniques":[51],"based":[52],"heuristics":[54],"or":[55],"human":[56],"perception":[57],"have":[58],"been":[59],"proposed,":[60],"both":[61],"for":[62,164,190,206],"traditional":[63],"flat":[64],"panel":[65],"displays":[66],"and":[67,74,85,106,143,198,204,219],"modern":[68],"modalities":[70],"such":[71],"as":[72,201],"virtual":[73],"augmented":[75],"reality":[76],"(VR/AR).":[77],"In":[78],"paper,":[80],"we":[81],"focus":[82],"developing":[84],"evaluating":[86],"power\u2010saving":[88],"that":[90,111,180],"use":[91],"machine":[92],"learning":[93,211],"(ML)":[94],"in":[95,154],"VR":[96,173],"displays.":[97],"We":[98],"developed":[99],"a":[100,129,145,186,202],"U\u2010Net\u2010based":[101],"technique":[102,168,184],"paired":[103],"with":[104,169],"perceptual":[105,155],"optimization":[108],"loss":[109],"functions":[110],"generates":[112],"spatially":[113],"varying":[114],"maps.":[116],"These":[117],"maps":[119],"are":[120],"input":[124],"images,":[125],"per\u2010pixel,":[126],"generate":[128],"power\u2010efficient":[130],"Our":[132,148,177],"pipeline":[133],"was":[134],"validated":[135],"via":[136],"quantitative":[137],"analysis":[138],"using":[139],"metrics":[142],"through":[144],"subjective":[146,149],"study.":[147],"validation":[150],"provides":[151],"results":[152,178],"scaled":[153],"just\u2010objectionable\u2010difference":[156],"(JOD)":[157],"units.":[158],"This":[159,196],"data,":[160],"when":[161],"rescaled,":[162],"allows":[163],"comparisons":[165],"our":[167,183],"recent":[170],"studies":[171],"optimization.":[176,215],"show":[179],"participants":[181],"prefer":[182],"over":[185],"uniform":[187],"baseline":[189,205],"high":[191],"target":[192],"saving":[194],"conditions.":[195],"model":[197],"study":[199],"serve":[200],"template":[203],"future":[207],"applications":[208],"deep":[210],"Model":[216],"training":[217],"code":[218],"data":[220],"found":[223],"at":[224],"kenchen10.github.io/projects/mlpea/index.html":[225],".":[226]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-08-01T09:00:35.917206","created_date":"2026-03-31T00:00:00"}