{"id":"https://openalex.org/W4319586068","doi":"https://doi.org/10.1109/candar57322.2022.00020","title":"A Bokeh Image Generation Technique using Machine Learning","display_name":"A Bokeh Image Generation Technique using Machine Learning","publication_year":2022,"publication_date":"2022-11-01","ids":{"openalex":"https://openalex.org/W4319586068","doi":"https://doi.org/10.1109/candar57322.2022.00020"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/candar57322.2022.00020","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},"type":"article","type_crossref":"proceedings-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/A5002923104","display_name":"Haiya Huang","orcid":null},"institutions":[{"id":"https://openalex.org/I113306721","display_name":"Hiroshima University","ror":"https://ror.org/03t78wx29","country_code":"JP","type":"education","lineage":["https://openalex.org/I113306721"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Haiya Huang","raw_affiliation_strings":["Graduate School of Advanced Science and Engineering, Hiroshima University,Higashi-hiroshima,Japan,739-8527"],"affiliations":[{"raw_affiliation_string":"Graduate School of Advanced Science and Engineering, Hiroshima University,Higashi-hiroshima,Japan,739-8527","institution_ids":["https://openalex.org/I113306721"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029487622","display_name":"Yasuaki Ito","orcid":"https://orcid.org/0000-0002-9189-8463"},"institutions":[{"id":"https://openalex.org/I113306721","display_name":"Hiroshima University","ror":"https://ror.org/03t78wx29","country_code":"JP","type":"education","lineage":["https://openalex.org/I113306721"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yasuaki Ito","raw_affiliation_strings":["Graduate School of Advanced Science and Engineering, Hiroshima University,Higashi-hiroshima,Japan,739-8527"],"affiliations":[{"raw_affiliation_string":"Graduate School of Advanced Science and Engineering, Hiroshima University,Higashi-hiroshima,Japan,739-8527","institution_ids":["https://openalex.org/I113306721"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5086055038","display_name":"Koji Nakano","orcid":"https://orcid.org/0000-0002-2040-4032"},"institutions":[{"id":"https://openalex.org/I113306721","display_name":"Hiroshima University","ror":"https://ror.org/03t78wx29","country_code":"JP","type":"education","lineage":["https://openalex.org/I113306721"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Koji Nakano","raw_affiliation_strings":["Graduate School of Advanced Science and Engineering, Hiroshima University,Higashi-hiroshima,Japan,739-8527"],"affiliations":[{"raw_affiliation_string":"Graduate School of Advanced Science and Engineering, Hiroshima University,Higashi-hiroshima,Japan,739-8527","institution_ids":["https://openalex.org/I113306721"]}]}],"institution_assertions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":0,"max":60},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","score":0.9995,"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":0.9995,"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/T13114","display_name":"Image Processing Techniques and Applications","score":0.9995,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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/T10531","display_name":"Advanced Vision and Imaging","score":0.9957,"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/aperture","display_name":"Aperture (computer memory)","score":0.48158097}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7771184},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7412755},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.66331357},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.61241084},{"id":"https://openalex.org/C119657128","wikidata":"https://www.wikidata.org/wiki/Q11633","display_name":"Photography","level":2,"score":0.52014714},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.4972146},{"id":"https://openalex.org/C78336883","wikidata":"https://www.wikidata.org/wiki/Q4779385","display_name":"Aperture (computer memory)","level":2,"score":0.48158097},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.48006663},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.08565965},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.08247441},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.07205358},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C153349607","wikidata":"https://www.wikidata.org/wiki/Q36649","display_name":"Visual arts","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/candar57322.2022.00020","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false}],"best_oa_location":null,"sustainable_development_goals":[],"grants":[],"datasets":[],"versions":[],"referenced_works_count":20,"referenced_works":["https://openalex.org/W1577807517","https://openalex.org/W1580389772","https://openalex.org/W1901129140","https://openalex.org/W2502312327","https://openalex.org/W2740099663","https://openalex.org/W2740994353","https://openalex.org/W2899663614","https://openalex.org/W2962785568","https://openalex.org/W2963760790","https://openalex.org/W3029088438","https://openalex.org/W3034960835","https://openalex.org/W3081752372","https://openalex.org/W3138516171","https://openalex.org/W3168491317","https://openalex.org/W3174957407","https://openalex.org/W3207918547","https://openalex.org/W3213290340","https://openalex.org/W4210465915","https://openalex.org/W4295312788","https://openalex.org/W4312443924"],"related_works":["https://openalex.org/W3007420330","https://openalex.org/W2990667865","https://openalex.org/W2891108385","https://openalex.org/W2527472564","https://openalex.org/W2154757407","https://openalex.org/W2141819204","https://openalex.org/W2028264897","https://openalex.org/W2005185696","https://openalex.org/W2004643608","https://openalex.org/W1511650216"],"abstract_inverted_index":{"In":[0,89],"photography,":[1],"bokeh":[2,27,61,109,125,154],"is":[3,12,53,131,175],"the":[4,103,115,124,150,166,172,182],"aesthetic":[5],"effect":[6,126],"appearing":[7],"in":[8,120],"out-of-focus":[9],"areas.":[10],"Bokeh":[11],"often":[13],"used":[14],"to":[15,20,42,54,58,91,114,122,133,139,158,178],"emphasize":[16],"a":[17,22,56,60,64,70,98,107,162],"subject":[18],"or":[19,179],"express":[21],"beautiful":[23],"background.":[24],"However,":[25],"such":[26],"effects":[28],"can":[29],"be":[30],"expressed":[31],"with":[32,35,44,161],"cameras":[33],"equipped":[34],"large-aperture":[36],"lenses":[37],"but":[38],"are":[39,111],"not":[40],"easy":[41],"realize":[43],"small-aperture":[45],"lenses.":[46],"The":[47,145],"main":[48],"contribution":[49],"of":[50,78,85,96],"this":[51],"paper":[52],"propose":[55,75],"technique":[57],"generate":[59],"image":[62,68,105,110],"from":[63,102],"single":[65],"overall":[66],"in-focus":[67],"using":[69,92],"machine":[71,136,184],"learning":[72,137,185],"approach.":[73],"We":[74],"two":[76,93],"types":[77,95],"U-Net":[79],"based":[80],"network":[81,116],"models,":[82],"mainly":[83],"composed":[84],"CNN":[86],"and":[87,106,138,142],"Transformer.":[88],"addition":[90],"different":[94],"networks,":[97],"depth":[99],"map":[100],"obtained":[101],"input":[104],"circular":[108],"also":[112],"provided":[113],"as":[117],"auxiliary":[118],"inputs":[119],"order":[121],"add":[123],"by":[127,135],"lens":[128],"aperture,":[129],"which":[130],"difficult":[132],"reproduce":[134],"distinguish":[140],"foreground":[141],"background":[143],"accurately.":[144],"experimental":[146],"results":[147,169],"show":[148,170],"that":[149,171],"proposed":[151,173],"method":[152,174],"produces":[153],"images":[155],"very":[156],"close":[157],"those":[159],"taken":[160],"real":[163],"camera.":[164],"Furthermore,":[165],"quantitative":[167],"evaluation":[168],"almost":[176],"equal":[177],"better":[180],"than":[181],"state-of-the-art":[183],"approaches.":[186]},"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W4319586068","counts_by_year":[],"updated_date":"2024-12-13T11:00:40.050275","created_date":"2023-02-09"}