{"id":"https://openalex.org/W4388726392","doi":"https://doi.org/10.1109/gcce59613.2023.10315341","title":"Object-Location Prediction based on CIE Color Difference for Deep Reinforcement Learning","display_name":"Object-Location Prediction based on CIE Color Difference for Deep Reinforcement Learning","publication_year":2023,"publication_date":"2023-10-10","ids":{"openalex":"https://openalex.org/W4388726392","doi":"https://doi.org/10.1109/gcce59613.2023.10315341"},"language":"en","primary_location":{"id":"doi:10.1109/gcce59613.2023.10315341","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/gcce59613.2023.10315341","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE 12th Global Conference on Consumer Electronics (GCCE)","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/A5101663984","display_name":"Kuan-Yi Li","orcid":"https://orcid.org/0000-0002-0320-2121"},"institutions":[{"id":"https://openalex.org/I99908691","display_name":"Yuan Ze University","ror":"https://ror.org/01fv1ds98","country_code":"TW","type":"education","lineage":["https://openalex.org/I99908691"]}],"countries":["TW"],"is_corresponding":true,"raw_author_name":"Kuan-Yi Li","raw_affiliation_strings":["Yuan Ze University,Department of Electrical Engineering,R.O.C.,32003"],"affiliations":[{"raw_affiliation_string":"Yuan Ze University,Department of Electrical Engineering,R.O.C.,32003","institution_ids":["https://openalex.org/I99908691"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103056563","display_name":"Shu-Yen Lin","orcid":"https://orcid.org/0000-0002-0537-9369"},"institutions":[{"id":"https://openalex.org/I99908691","display_name":"Yuan Ze University","ror":"https://ror.org/01fv1ds98","country_code":"TW","type":"education","lineage":["https://openalex.org/I99908691"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Shu-Yen Lin","raw_affiliation_strings":["Yuan Ze University,Department of Electrical Engineering,R.O.C.,32003"],"affiliations":[{"raw_affiliation_string":"Yuan Ze University,Department of Electrical Engineering,R.O.C.,32003","institution_ids":["https://openalex.org/I99908691"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5101663984"],"corresponding_institution_ids":["https://openalex.org/I99908691"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.15734732,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"392","last_page":"393"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11666","display_name":"Color Science and Applications","score":0.998199999332428,"subfield":{"id":"https://openalex.org/subfields/3107","display_name":"Atomic and Molecular Physics, and Optics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11666","display_name":"Color Science and Applications","score":0.998199999332428,"subfield":{"id":"https://openalex.org/subfields/3107","display_name":"Atomic and Molecular Physics, and Optics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","score":0.9972000122070312,"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/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9972000122070312,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.7487428784370422},{"id":"https://openalex.org/keywords/color-difference","display_name":"Color difference","score":0.7387349605560303},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.7345290184020996},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6893939971923828},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.648175835609436},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6461449861526489},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.4814719259738922},{"id":"https://openalex.org/keywords/significant-difference","display_name":"Significant difference","score":0.43786245584487915},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.39778146147727966},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.28344348073005676},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.0854329764842987}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7487428784370422},{"id":"https://openalex.org/C186991048","wikidata":"https://www.wikidata.org/wiki/Q1184883","display_name":"Color difference","level":3,"score":0.7387349605560303},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.7345290184020996},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6893939971923828},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.648175835609436},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6461449861526489},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.4814719259738922},{"id":"https://openalex.org/C3018023364","wikidata":"https://www.wikidata.org/wiki/Q425265","display_name":"Significant difference","level":2,"score":0.43786245584487915},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.39778146147727966},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.28344348073005676},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0854329764842987},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/gcce59613.2023.10315341","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/gcce59613.2023.10315341","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE 12th Global Conference on Consumer Electronics (GCCE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320331164","display_name":"National Science and Technology Council","ror":"https://ror.org/00wnb9798"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":9,"referenced_works":["https://openalex.org/W2000512760","https://openalex.org/W3013713530","https://openalex.org/W3046996480","https://openalex.org/W3100789280","https://openalex.org/W3177023213","https://openalex.org/W4292387400","https://openalex.org/W4362650357","https://openalex.org/W6650486518","https://openalex.org/W6841783073"],"related_works":["https://openalex.org/W2355916073","https://openalex.org/W2297890168","https://openalex.org/W2932608023","https://openalex.org/W2378646418","https://openalex.org/W2060944080","https://openalex.org/W2378735648","https://openalex.org/W2113785300","https://openalex.org/W2240460439","https://openalex.org/W2360502356","https://openalex.org/W2224396262"],"abstract_inverted_index":{"In":[0,48],"this":[1],"work,":[2],"we":[3],"propose":[4],"an":[5],"Object-Location":[6],"Prediction":[7],"based":[8,31],"on":[9,15,32],"Color":[10],"Difference":[11],"from":[12],"International":[13],"Commission":[14],"Illumination":[16],"(OLP-CIE)":[17],"to":[18,56,98],"predict":[19],"the":[20,23,26,36,39,43,50,60,64,68,72,78,82,85,91,94,99,102],"location":[21,30,83],"of":[22,38,63,71,84,93,104],"object":[24,65,86],"in":[25],"image.":[27],"The":[28],"predicted":[29,89],"OLP-CIE":[33,105],"can":[34,87,106],"improve":[35],"iterations":[37],"training":[40],"steps":[41],"for":[42],"deep":[44],"reinforcement":[45],"learning":[46],"(DRL).":[47],"OLP-CIE,":[49],"CIEDE":[51],"2000":[52],"formula":[53],"is":[54,75],"used":[55],"compare":[57],"and":[58,112],"calculate":[59],"color":[61,73],"difference":[62,74],"color.":[66],"Then,":[67],"calculation":[69],"result":[70],"converted":[76],"into":[77],"feature":[79,95],"map.":[80,96],"Finally,":[81],"be":[88,107],"by":[90],"analysis":[92],"Compared":[97],"related":[100],"works,":[101],"accuracy":[103],"maintained":[108],"with":[109],"simpler":[110],"algorithm":[111],"fewer":[113],"hardware":[114],"operations.":[115]},"counts_by_year":[],"updated_date":"2025-12-25T23:11:45.687758","created_date":"2025-10-10T00:00:00"}
