{"id":"https://openalex.org/W4312650395","doi":"https://doi.org/10.1109/icpr56361.2022.9956598","title":"PyNet-V2 Mobile: Efficient On-Device Photo Processing With Neural Networks","display_name":"PyNet-V2 Mobile: Efficient On-Device Photo Processing With Neural Networks","publication_year":2022,"publication_date":"2022-08-21","ids":{"openalex":"https://openalex.org/W4312650395","doi":"https://doi.org/10.1109/icpr56361.2022.9956598"},"language":"en","primary_location":{"id":"doi:10.1109/icpr56361.2022.9956598","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr56361.2022.9956598","pdf_url":null,"source":{"id":"https://openalex.org/S4363607731","display_name":"2022 26th International Conference on Pattern Recognition (ICPR)","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 26th International Conference on Pattern Recognition (ICPR)","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/A5022836568","display_name":"Andrey Ignatov","orcid":"https://orcid.org/0000-0003-4205-8748"},"institutions":[{"id":"https://openalex.org/I35440088","display_name":"ETH Zurich","ror":"https://ror.org/05a28rw58","country_code":"CH","type":"education","lineage":["https://openalex.org/I2799323385","https://openalex.org/I35440088"]}],"countries":["CH"],"is_corresponding":true,"raw_author_name":"Andrey Ignatov","raw_affiliation_strings":["ETH Zurich,Computer Vision Laboratory,Switzerland","Computer Vision Laboratory, ETH Zurich, Switzerland","AI Witchlabs Ltd., Zollikerberg, Switzerland"],"affiliations":[{"raw_affiliation_string":"ETH Zurich,Computer Vision Laboratory,Switzerland","institution_ids":["https://openalex.org/I35440088"]},{"raw_affiliation_string":"Computer Vision Laboratory, ETH Zurich, Switzerland","institution_ids":["https://openalex.org/I35440088"]},{"raw_affiliation_string":"AI Witchlabs Ltd., Zollikerberg, Switzerland","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015944776","display_name":"Grigory Malivenko","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Grigory Malivenko","raw_affiliation_strings":["AI Witchlabs Ltd.,Zollikerberg,Switzerland","AI Witchlabs Ltd., Zollikerberg, Switzerland"],"affiliations":[{"raw_affiliation_string":"AI Witchlabs Ltd.,Zollikerberg,Switzerland","institution_ids":[]},{"raw_affiliation_string":"AI Witchlabs Ltd., Zollikerberg, Switzerland","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052236177","display_name":"Radu Timofte","orcid":"https://orcid.org/0000-0002-1478-0402"},"institutions":[{"id":"https://openalex.org/I35440088","display_name":"ETH Zurich","ror":"https://ror.org/05a28rw58","country_code":"CH","type":"education","lineage":["https://openalex.org/I2799323385","https://openalex.org/I35440088"]}],"countries":["CH"],"is_corresponding":false,"raw_author_name":"Radu Timofte","raw_affiliation_strings":["ETH Zurich,Computer Vision Laboratory,Switzerland","AI Witchlabs Ltd., Zollikerberg, Switzerland","Computer Vision Laboratory, ETH Zurich, Switzerland"],"affiliations":[{"raw_affiliation_string":"ETH Zurich,Computer Vision Laboratory,Switzerland","institution_ids":["https://openalex.org/I35440088"]},{"raw_affiliation_string":"AI Witchlabs Ltd., Zollikerberg, Switzerland","institution_ids":[]},{"raw_affiliation_string":"Computer Vision Laboratory, ETH Zurich, Switzerland","institution_ids":["https://openalex.org/I35440088"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112685116","display_name":"Yu Tseng","orcid":null},"institutions":[{"id":"https://openalex.org/I4210148979","display_name":"MediaTek (Taiwan)","ror":"https://ror.org/05g9jck81","country_code":"TW","type":"company","lineage":["https://openalex.org/I4210148979"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Yu Tseng","raw_affiliation_strings":["MediaTek Inc.,Hsinchu,Taiwan","MediaTek Inc., Hsinchu, Taiwan"],"affiliations":[{"raw_affiliation_string":"MediaTek Inc.,Hsinchu,Taiwan","institution_ids":["https://openalex.org/I4210148979"]},{"raw_affiliation_string":"MediaTek Inc., Hsinchu, Taiwan","institution_ids":["https://openalex.org/I4210148979"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101236500","display_name":"Yu-Syuan Xu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210148979","display_name":"MediaTek (Taiwan)","ror":"https://ror.org/05g9jck81","country_code":"TW","type":"company","lineage":["https://openalex.org/I4210148979"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Yu-Syuan Xu","raw_affiliation_strings":["MediaTek Inc.,Hsinchu,Taiwan","MediaTek Inc., Hsinchu, Taiwan"],"affiliations":[{"raw_affiliation_string":"MediaTek Inc.,Hsinchu,Taiwan","institution_ids":["https://openalex.org/I4210148979"]},{"raw_affiliation_string":"MediaTek Inc., Hsinchu, Taiwan","institution_ids":["https://openalex.org/I4210148979"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015572561","display_name":"Po\u2010Hsiang Yu","orcid":"https://orcid.org/0000-0001-6561-305X"},"institutions":[{"id":"https://openalex.org/I4210148979","display_name":"MediaTek (Taiwan)","ror":"https://ror.org/05g9jck81","country_code":"TW","type":"company","lineage":["https://openalex.org/I4210148979"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Po-Hsiang Yu","raw_affiliation_strings":["MediaTek Inc.,Hsinchu,Taiwan","MediaTek Inc., Hsinchu, Taiwan"],"affiliations":[{"raw_affiliation_string":"MediaTek Inc.,Hsinchu,Taiwan","institution_ids":["https://openalex.org/I4210148979"]},{"raw_affiliation_string":"MediaTek Inc., Hsinchu, Taiwan","institution_ids":["https://openalex.org/I4210148979"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024646639","display_name":"Cheng\u2010Ming Chiang","orcid":"https://orcid.org/0000-0002-4968-3282"},"institutions":[{"id":"https://openalex.org/I4210148979","display_name":"MediaTek (Taiwan)","ror":"https://ror.org/05g9jck81","country_code":"TW","type":"company","lineage":["https://openalex.org/I4210148979"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Cheng-Ming Chiang","raw_affiliation_strings":["MediaTek Inc.,Hsinchu,Taiwan","MediaTek Inc., Hsinchu, Taiwan"],"affiliations":[{"raw_affiliation_string":"MediaTek Inc.,Hsinchu,Taiwan","institution_ids":["https://openalex.org/I4210148979"]},{"raw_affiliation_string":"MediaTek Inc., Hsinchu, Taiwan","institution_ids":["https://openalex.org/I4210148979"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108201154","display_name":"Hsien-Kai Kuo","orcid":null},"institutions":[{"id":"https://openalex.org/I4210148979","display_name":"MediaTek (Taiwan)","ror":"https://ror.org/05g9jck81","country_code":"TW","type":"company","lineage":["https://openalex.org/I4210148979"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Hsien-Kai Kuo","raw_affiliation_strings":["MediaTek Inc.,Hsinchu,Taiwan","MediaTek Inc., Hsinchu, Taiwan"],"affiliations":[{"raw_affiliation_string":"MediaTek Inc.,Hsinchu,Taiwan","institution_ids":["https://openalex.org/I4210148979"]},{"raw_affiliation_string":"MediaTek Inc., Hsinchu, Taiwan","institution_ids":["https://openalex.org/I4210148979"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076820670","display_name":"Min-Hung Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I4210148979","display_name":"MediaTek (Taiwan)","ror":"https://ror.org/05g9jck81","country_code":"TW","type":"company","lineage":["https://openalex.org/I4210148979"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Min-Hung Chen","raw_affiliation_strings":["MediaTek Inc.,Hsinchu,Taiwan","MediaTek Inc., Hsinchu, Taiwan"],"affiliations":[{"raw_affiliation_string":"MediaTek Inc.,Hsinchu,Taiwan","institution_ids":["https://openalex.org/I4210148979"]},{"raw_affiliation_string":"MediaTek Inc., Hsinchu, Taiwan","institution_ids":["https://openalex.org/I4210148979"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109121547","display_name":"Chia-Ming Cheng","orcid":null},"institutions":[{"id":"https://openalex.org/I4210148979","display_name":"MediaTek (Taiwan)","ror":"https://ror.org/05g9jck81","country_code":"TW","type":"company","lineage":["https://openalex.org/I4210148979"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Chia-Ming Cheng","raw_affiliation_strings":["MediaTek Inc.,Hsinchu,Taiwan","MediaTek Inc., Hsinchu, Taiwan"],"affiliations":[{"raw_affiliation_string":"MediaTek Inc.,Hsinchu,Taiwan","institution_ids":["https://openalex.org/I4210148979"]},{"raw_affiliation_string":"MediaTek Inc., Hsinchu, Taiwan","institution_ids":["https://openalex.org/I4210148979"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5001254143","display_name":"Luc Van Gool","orcid":"https://orcid.org/0000-0002-3445-5711"},"institutions":[{"id":"https://openalex.org/I35440088","display_name":"ETH Zurich","ror":"https://ror.org/05a28rw58","country_code":"CH","type":"education","lineage":["https://openalex.org/I2799323385","https://openalex.org/I35440088"]}],"countries":["CH"],"is_corresponding":false,"raw_author_name":"Luc Van Gool","raw_affiliation_strings":["ETH Zurich,Computer Vision Laboratory,Switzerland","Computer Vision Laboratory, ETH Zurich, Switzerland","AI Witchlabs Ltd., Zollikerberg, Switzerland"],"affiliations":[{"raw_affiliation_string":"ETH Zurich,Computer Vision Laboratory,Switzerland","institution_ids":["https://openalex.org/I35440088"]},{"raw_affiliation_string":"Computer Vision Laboratory, ETH Zurich, Switzerland","institution_ids":["https://openalex.org/I35440088"]},{"raw_affiliation_string":"AI Witchlabs Ltd., Zollikerberg, Switzerland","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":11,"corresponding_author_ids":["https://openalex.org/A5022836568"],"corresponding_institution_ids":["https://openalex.org/I35440088"],"apc_list":null,"apc_paid":null,"fwci":1.5581,"has_fulltext":false,"cited_by_count":27,"citation_normalized_percentile":{"value":0.88820761,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"677","last_page":"684"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","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/T11105","display_name":"Advanced Image Processing Techniques","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/T10531","display_name":"Advanced Vision and Imaging","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/T11019","display_name":"Image Enhancement Techniques","score":0.9995999932289124,"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":0.8553614020347595},{"id":"https://openalex.org/keywords/mobile-device","display_name":"Mobile device","score":0.6412084698677063},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.605297863483429},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.5819349884986877},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5567365884780884},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.5312625765800476},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.45035940408706665},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.4460153877735138},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.42457136511802673},{"id":"https://openalex.org/keywords/mobile-computing","display_name":"Mobile computing","score":0.42306947708129883},{"id":"https://openalex.org/keywords/pipeline-transport","display_name":"Pipeline transport","score":0.4108726382255554},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.3342362344264984},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.23549827933311462},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.11946627497673035}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8553614020347595},{"id":"https://openalex.org/C186967261","wikidata":"https://www.wikidata.org/wiki/Q5082128","display_name":"Mobile device","level":2,"score":0.6412084698677063},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.605297863483429},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.5819349884986877},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5567365884780884},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.5312625765800476},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.45035940408706665},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.4460153877735138},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.42457136511802673},{"id":"https://openalex.org/C144543869","wikidata":"https://www.wikidata.org/wiki/Q2738570","display_name":"Mobile computing","level":2,"score":0.42306947708129883},{"id":"https://openalex.org/C175309249","wikidata":"https://www.wikidata.org/wiki/Q725864","display_name":"Pipeline transport","level":2,"score":0.4108726382255554},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.3342362344264984},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.23549827933311462},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.11946627497673035},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C87717796","wikidata":"https://www.wikidata.org/wiki/Q146326","display_name":"Environmental engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icpr56361.2022.9956598","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr56361.2022.9956598","pdf_url":null,"source":{"id":"https://openalex.org/S4363607731","display_name":"2022 26th International Conference on Pattern Recognition (ICPR)","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 26th International Conference on Pattern Recognition (ICPR)","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":0.5}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":68,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1547836497","https://openalex.org/W1885185971","https://openalex.org/W1901129140","https://openalex.org/W1920280450","https://openalex.org/W2025134675","https://openalex.org/W2156159690","https://openalex.org/W2165107586","https://openalex.org/W2242218935","https://openalex.org/W2331128040","https://openalex.org/W2412926690","https://openalex.org/W2503339013","https://openalex.org/W2508457857","https://openalex.org/W2607202125","https://openalex.org/W2739757502","https://openalex.org/W2764207251","https://openalex.org/W2783573276","https://openalex.org/W2891158090","https://openalex.org/W2895432151","https://openalex.org/W2895518292","https://openalex.org/W2911581663","https://openalex.org/W2912096748","https://openalex.org/W2913277259","https://openalex.org/W2914930131","https://openalex.org/W2915130236","https://openalex.org/W2954506705","https://openalex.org/W2962785568","https://openalex.org/W2963073614","https://openalex.org/W2963372104","https://openalex.org/W2963446712","https://openalex.org/W2963470893","https://openalex.org/W2963594255","https://openalex.org/W2963762505","https://openalex.org/W2964125708","https://openalex.org/W2967997213","https://openalex.org/W2980876396","https://openalex.org/W2996870660","https://openalex.org/W2998506323","https://openalex.org/W3012322483","https://openalex.org/W3034328879","https://openalex.org/W3034448817","https://openalex.org/W3034595214","https://openalex.org/W3034960835","https://openalex.org/W3035381835","https://openalex.org/W3127229141","https://openalex.org/W3127617232","https://openalex.org/W3134235012","https://openalex.org/W3135799625","https://openalex.org/W3167674261","https://openalex.org/W3173285755","https://openalex.org/W3173515979","https://openalex.org/W3175157054","https://openalex.org/W3177327133","https://openalex.org/W6631190155","https://openalex.org/W6639824700","https://openalex.org/W6690498163","https://openalex.org/W6725739302","https://openalex.org/W6729966448","https://openalex.org/W6742864230","https://openalex.org/W6754405603","https://openalex.org/W6754913113","https://openalex.org/W6755325935","https://openalex.org/W6758440325","https://openalex.org/W6758665117","https://openalex.org/W6758764439","https://openalex.org/W6759798451","https://openalex.org/W6790097491","https://openalex.org/W6795364465"],"related_works":["https://openalex.org/W4380433113","https://openalex.org/W4386072068","https://openalex.org/W252339960","https://openalex.org/W2390529043","https://openalex.org/W2378320433","https://openalex.org/W2358343511","https://openalex.org/W2051877971","https://openalex.org/W1787170397","https://openalex.org/W4292347844","https://openalex.org/W2330191542"],"abstract_inverted_index":{"The":[0,129,198],"increased":[1],"importance":[2],"of":[3,18,25,96,110,142,189],"mobile":[4,27,78,126,172],"photography":[5],"created":[6],"a":[7,58,116,123],"need":[8],"for":[9,47,66,155],"fast":[10,156],"and":[11,83,91,122,201],"performant":[12],"RAW":[13,73],"image":[14,50,112,157],"processing":[15],"pipelines":[16],"capable":[17],"producing":[19,84],"good":[20],"visual":[21],"results":[22,130],"in":[23,205],"spite":[24],"the":[26,94,97,102,133,140,148,163,170,187,190,211],"camera":[28,121,127],"sensor":[29],"limitations.":[30],"While":[31],"deep":[32],"learning-based":[33],"approaches":[34],"can":[35,137,181],"efficiently":[36],"solve":[37],"this":[38,54,206],"problem,":[39],"their":[40],"computational":[41],"requirements":[42],"usually":[43],"remain":[44],"too":[45],"large":[46],"high-resolution":[48],"on-device":[49],"processing.":[51,158],"To":[52,89],"address":[53],"limitation,":[55],"we":[56,100,160],"propose":[57],"novel":[59],"PyNET-V2":[60,134],"Mobile":[61,135],"CNN":[62],"architecture":[63,165],"designed":[64,154],"specifically":[65],"edge":[67],"devices,":[68],"being":[69],"able":[70],"to":[71,92,184,192],"process":[72],"12MP":[74],"photos":[75],"directly":[76],"on":[77,108,210],"phones":[79],"under":[80],"1.5":[81],"second":[82],"high":[85],"perceptual":[86],"photo":[87],"quality.":[88],"train":[90],"evaluate":[93],"performance":[95],"proposed":[98,164],"solution,":[99],"use":[101],"real-world":[103],"Fujifilm":[104,120],"UltraISP":[105],"dataset":[106],"consisting":[107],"thousands":[109],"RAW-RGB":[111],"pairs":[113],"captured":[114],"with":[115,169],"professional":[117],"medium-format":[118],"102MP":[119],"popular":[124],"Sony":[125],"sensor.":[128],"demonstrate":[131],"that":[132,162,180],"model":[136,191],"substantially":[138],"surpass":[139],"quality":[141],"tradition":[143],"ISP":[144],"pipelines,":[145],"while":[146],"outperforming":[147],"previously":[149],"introduced":[150],"neural":[151],"network-based":[152],"solutions":[153],"Furthermore,":[159],"show":[161],"is":[166],"also":[167],"compatible":[168],"latest":[171],"AI":[173],"accelerators":[174],"such":[175],"as":[176,193,195],"NPUs":[177],"or":[178],"APUs":[179],"be":[182],"used":[183,204],"further":[185],"reduce":[186],"latency":[188],"little":[194],"0.5":[196],"second.":[197],"dataset,":[199],"code":[200],"pre-trained":[202],"models":[203],"paper":[207],"are":[208],"available":[209],"project":[212],"website:":[213],"https://github.com/gmalivenko/PyNET-v2":[214]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":10},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":10}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}