{"id":"https://openalex.org/W3106695176","doi":"https://doi.org/10.1109/icce-taiwan49838.2020.9258094","title":"Autoencoder-based Image Companding","display_name":"Autoencoder-based Image Companding","publication_year":2020,"publication_date":"2020-09-28","ids":{"openalex":"https://openalex.org/W3106695176","doi":"https://doi.org/10.1109/icce-taiwan49838.2020.9258094","mag":"3106695176"},"language":"en","primary_location":{"id":"doi:10.1109/icce-taiwan49838.2020.9258094","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icce-taiwan49838.2020.9258094","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Consumer Electronics - Taiwan (ICCE-Taiwan)","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/A5112584412","display_name":"Alim Wicaksono H.P.","orcid":null},"institutions":[{"id":"https://openalex.org/I119896790","display_name":"Sebelas Maret University","ror":"https://ror.org/021hq5q33","country_code":"ID","type":"education","lineage":["https://openalex.org/I119896790"]}],"countries":["ID"],"is_corresponding":true,"raw_author_name":"Alim Wicaksono H.P.","raw_affiliation_strings":["Universitas Sebelas Maret (UNS), Surakarta, Indonesia"],"affiliations":[{"raw_affiliation_string":"Universitas Sebelas Maret (UNS), Surakarta, Indonesia","institution_ids":["https://openalex.org/I119896790"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004946227","display_name":"Heri Prasetyo","orcid":"https://orcid.org/0000-0002-1257-4832"},"institutions":[{"id":"https://openalex.org/I119896790","display_name":"Sebelas Maret University","ror":"https://ror.org/021hq5q33","country_code":"ID","type":"education","lineage":["https://openalex.org/I119896790"]}],"countries":["ID"],"is_corresponding":false,"raw_author_name":"Heri Prasetyo","raw_affiliation_strings":["Universitas Sebelas Maret (UNS), Surakarta, Indonesia"],"affiliations":[{"raw_affiliation_string":"Universitas Sebelas Maret (UNS), Surakarta, Indonesia","institution_ids":["https://openalex.org/I119896790"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5033900220","display_name":"Jing-Ming Guo","orcid":"https://orcid.org/0000-0001-7764-964X"},"institutions":[{"id":"https://openalex.org/I154864474","display_name":"National Taiwan University of Science and Technology","ror":"https://ror.org/00q09pe49","country_code":"TW","type":"education","lineage":["https://openalex.org/I154864474"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Jing-Ming Guo","raw_affiliation_strings":["National Taiwan University of Science and Technology, Taipei, Taiwan"],"affiliations":[{"raw_affiliation_string":"National Taiwan University of Science and Technology, Taipei, Taiwan","institution_ids":["https://openalex.org/I154864474"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5112584412"],"corresponding_institution_ids":["https://openalex.org/I119896790"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.13211669,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"2"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11019","display_name":"Image Enhancement Techniques","score":0.9998000264167786,"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/T11019","display_name":"Image Enhancement Techniques","score":0.9998000264167786,"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/T10688","display_name":"Image and Signal Denoising Methods","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"}},{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","score":0.9987000226974487,"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/companding","display_name":"Companding","score":0.9895176887512207},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.9025901556015015},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7843472957611084},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.6761583685874939},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6141465902328491},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6029309034347534},{"id":"https://openalex.org/keywords/high-dynamic-range","display_name":"High dynamic range","score":0.6003164649009705},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5599156618118286},{"id":"https://openalex.org/keywords/dynamic-range","display_name":"Dynamic range","score":0.5372306108474731},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5348898768424988},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5329253077507019},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.49199554324150085},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.45707258582115173},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.4249856770038605},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3586820662021637},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.357807457447052},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.31226083636283875},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.09263765811920166},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.059965550899505615}],"concepts":[{"id":"https://openalex.org/C104250799","wikidata":"https://www.wikidata.org/wiki/Q1780765","display_name":"Companding","level":4,"score":0.9895176887512207},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.9025901556015015},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7843472957611084},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.6761583685874939},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6141465902328491},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6029309034347534},{"id":"https://openalex.org/C2780056265","wikidata":"https://www.wikidata.org/wiki/Q106239881","display_name":"High dynamic range","level":3,"score":0.6003164649009705},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5599156618118286},{"id":"https://openalex.org/C87133666","wikidata":"https://www.wikidata.org/wiki/Q1161699","display_name":"Dynamic range","level":2,"score":0.5372306108474731},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5348898768424988},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5329253077507019},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.49199554324150085},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.45707258582115173},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.4249856770038605},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3586820662021637},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.357807457447052},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.31226083636283875},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.09263765811920166},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.059965550899505615},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.0},{"id":"https://openalex.org/C40409654","wikidata":"https://www.wikidata.org/wiki/Q375889","display_name":"Orthogonal frequency-division multiplexing","level":3,"score":0.0},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icce-taiwan49838.2020.9258094","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icce-taiwan49838.2020.9258094","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Consumer Electronics - Taiwan (ICCE-Taiwan)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":5,"referenced_works":["https://openalex.org/W314258864","https://openalex.org/W2302255633","https://openalex.org/W2344536484","https://openalex.org/W2731904314","https://openalex.org/W2740336064"],"related_works":["https://openalex.org/W2092035358","https://openalex.org/W2087695345","https://openalex.org/W2884377208","https://openalex.org/W2105254225","https://openalex.org/W2525745698","https://openalex.org/W2010724756","https://openalex.org/W2152030049","https://openalex.org/W2061818168","https://openalex.org/W4234463037","https://openalex.org/W2564543331"],"abstract_inverted_index":{"This":[0],"paper":[1],"presents":[2],"a":[3,73],"deep":[4],"learning-based":[5],"method":[6,71],"for":[7],"effective":[8],"image":[9,43],"companding.":[10],"The":[11,63],"autoencoder":[12],"inherits":[13],"the":[14,42,47,51,69],"effectiveness":[15],"of":[16],"Convolutional":[17],"Neural":[18],"Networks":[19],"(CNN)":[20],"and":[21,37,53],"residual":[22],"learning":[23],"framework":[24],"to":[25,32],"transform":[26],"High":[27],"Dynamic":[28,34],"Range":[29,35],"(HDR)":[30],"images":[31],"Low":[33],"(LDR)":[36],"its":[38],"reverse":[39],"process.":[40],"Since,":[41],"companding":[44],"task":[45],"involves":[46],"nondifferentiable":[48],"operation,":[49],"thus":[50],"encoder":[52],"decoder":[54],"networks":[55],"are":[56],"alternately":[57],"trained":[58],"using":[59],"an":[60],"iterative":[61],"approach.":[62],"experimental":[64],"result":[65],"clearly":[66],"reveals":[67],"that":[68],"proposed":[70],"yields":[72],"promising":[74],"result.":[75]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}