{"id":"https://openalex.org/W2943316151","doi":"https://doi.org/10.1145/3313950.3313965","title":"Densely connected AutoEncoders for image compression","display_name":"Densely connected AutoEncoders for image compression","publication_year":2019,"publication_date":"2019-02-23","ids":{"openalex":"https://openalex.org/W2943316151","doi":"https://doi.org/10.1145/3313950.3313965","mag":"2943316151"},"language":"en","primary_location":{"id":"doi:10.1145/3313950.3313965","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3313950.3313965","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2nd International Conference on Image and Graphics Processing","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/A5084965932","display_name":"Song Zebang","orcid":null},"institutions":[{"id":"https://openalex.org/I150744194","display_name":"Waseda University","ror":"https://ror.org/00ntfnx83","country_code":"JP","type":"education","lineage":["https://openalex.org/I150744194"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Song Zebang","raw_affiliation_strings":["Waseda University, Kitakyushu, Fukuoka, Japan"],"affiliations":[{"raw_affiliation_string":"Waseda University, Kitakyushu, Fukuoka, Japan","institution_ids":["https://openalex.org/I150744194"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5066452160","display_name":"Sei\u2010ichiro Kamata","orcid":"https://orcid.org/0000-0002-1496-2417"},"institutions":[{"id":"https://openalex.org/I150744194","display_name":"Waseda University","ror":"https://ror.org/00ntfnx83","country_code":"JP","type":"education","lineage":["https://openalex.org/I150744194"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Kamata Sei-ichiro","raw_affiliation_strings":["Waseda University, Kitakyushu, Fukuoka, Japan"],"affiliations":[{"raw_affiliation_string":"Waseda University, Kitakyushu, Fukuoka, Japan","institution_ids":["https://openalex.org/I150744194"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5084965932"],"corresponding_institution_ids":["https://openalex.org/I150744194"],"apc_list":null,"apc_paid":null,"fwci":0.911,"has_fulltext":false,"cited_by_count":20,"citation_normalized_percentile":{"value":0.78653462,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"78","last_page":"83"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","score":1.0,"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":1.0,"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":0.9997000098228455,"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/T10901","display_name":"Advanced Data Compression Techniques","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"}}],"keywords":[{"id":"https://openalex.org/keywords/lossy-compression","display_name":"Lossy compression","score":0.8612388372421265},{"id":"https://openalex.org/keywords/image-compression","display_name":"Image compression","score":0.8329565525054932},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7596579790115356},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.745681643486023},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.724324643611908},{"id":"https://openalex.org/keywords/jpeg-2000","display_name":"JPEG 2000","score":0.6793617010116577},{"id":"https://openalex.org/keywords/jpeg","display_name":"JPEG","score":0.6515932679176331},{"id":"https://openalex.org/keywords/texture-compression","display_name":"Texture compression","score":0.6437751054763794},{"id":"https://openalex.org/keywords/data-compression","display_name":"Data compression","score":0.6236332058906555},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5956639051437378},{"id":"https://openalex.org/keywords/data-compression-ratio","display_name":"Data compression ratio","score":0.5269972681999207},{"id":"https://openalex.org/keywords/compression","display_name":"Compression (physics)","score":0.44709840416908264},{"id":"https://openalex.org/keywords/lossless-compression","display_name":"Lossless compression","score":0.42903733253479004},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.38823381066322327},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.34084248542785645},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.31714367866516113},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.2890186309814453}],"concepts":[{"id":"https://openalex.org/C165021410","wikidata":"https://www.wikidata.org/wiki/Q55564","display_name":"Lossy compression","level":2,"score":0.8612388372421265},{"id":"https://openalex.org/C13481523","wikidata":"https://www.wikidata.org/wiki/Q412438","display_name":"Image compression","level":4,"score":0.8329565525054932},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7596579790115356},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.745681643486023},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.724324643611908},{"id":"https://openalex.org/C69216139","wikidata":"https://www.wikidata.org/wiki/Q931783","display_name":"JPEG 2000","level":5,"score":0.6793617010116577},{"id":"https://openalex.org/C198751489","wikidata":"https://www.wikidata.org/wiki/Q2195","display_name":"JPEG","level":3,"score":0.6515932679176331},{"id":"https://openalex.org/C54243161","wikidata":"https://www.wikidata.org/wiki/Q39333","display_name":"Texture compression","level":5,"score":0.6437751054763794},{"id":"https://openalex.org/C78548338","wikidata":"https://www.wikidata.org/wiki/Q2493","display_name":"Data compression","level":2,"score":0.6236332058906555},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5956639051437378},{"id":"https://openalex.org/C94835093","wikidata":"https://www.wikidata.org/wiki/Q3113333","display_name":"Data compression ratio","level":5,"score":0.5269972681999207},{"id":"https://openalex.org/C180016635","wikidata":"https://www.wikidata.org/wiki/Q2712821","display_name":"Compression (physics)","level":2,"score":0.44709840416908264},{"id":"https://openalex.org/C81081738","wikidata":"https://www.wikidata.org/wiki/Q55542","display_name":"Lossless compression","level":3,"score":0.42903733253479004},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.38823381066322327},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.34084248542785645},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.31714367866516113},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2890186309814453},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3313950.3313965","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3313950.3313965","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2nd International Conference on Image and Graphics Processing","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":14,"referenced_works":["https://openalex.org/W1885185971","https://openalex.org/W1901129140","https://openalex.org/W2276024283","https://openalex.org/W2476548250","https://openalex.org/W2593493485","https://openalex.org/W2604392022","https://openalex.org/W2613896470","https://openalex.org/W2950237263","https://openalex.org/W2962949190","https://openalex.org/W2963149687","https://openalex.org/W2963446712","https://openalex.org/W2963470893","https://openalex.org/W6725739302","https://openalex.org/W6736182379"],"related_works":["https://openalex.org/W2013943429","https://openalex.org/W2353117054","https://openalex.org/W2096442341","https://openalex.org/W2380116549","https://openalex.org/W2342447567","https://openalex.org/W1680283075","https://openalex.org/W4239869440","https://openalex.org/W2549477129","https://openalex.org/W3162084246","https://openalex.org/W3208328673"],"abstract_inverted_index":{"Image":[0],"compression,":[1,176],"which":[2,31,98,139],"is":[3,75,163],"a":[4,15,93,110,116,128,148,190],"type":[5],"of":[6,29,40,46,102,169],"data":[7,42],"compression":[8,51,59,85,96],"applied":[9],"to":[10,36,108,132,152,165],"digital":[11],"images,":[12],"has":[13,65],"been":[14],"fundamental":[16],"research":[17],"topic":[18],"for":[19,121,143],"many":[20,70],"decades.":[21],"Recent":[22],"image":[23,41,80,95,123,138,175],"techniques":[24],"produce":[25,189],"very":[26],"large":[27],"amounts":[28],"data,":[30],"may":[32,56],"make":[33],"it":[34],"prohibitive":[35],"storage":[37],"and":[38,74,185,187,199],"communications":[39],"without":[43],"the":[44,49,58,84,100,103,154,167],"use":[45],"compression.":[47,81,124,144,158],"However,":[48],"traditional":[50],"methods,":[52],"such":[53],"as":[54],"JPEG,":[55],"introduce":[57],"artefact":[60],"problems.":[61],"Recently,":[62],"deep":[63,105],"learning":[64,106],"achieved":[66],"great":[67],"success":[68],"in":[69,79,88],"computer":[71],"vision":[72],"tasks":[73],"gradually":[76],"being":[77],"used":[78],"To":[82],"solve":[83],"atrefact":[86],"problem,":[87],"this":[89],"paper,":[90],"we":[91,126,146],"present":[92],"lossy":[94,122],"architecture,":[97],"utilizes":[99],"advantages":[101],"existing":[104],"methods":[107],"achieve":[109],"high":[111],"coding":[112],"efficiency.":[113],"We":[114],"design":[115,127,147],"densely":[117,129],"connected":[118],"autoencoder":[119,130],"structure":[120,131],"Firstly,":[125],"get":[133],"richer":[134],"feature":[135],"information":[136],"from":[137],"can":[140,188],"be":[141],"helpful":[142],"Secondly,":[145],"U-net":[149],"like":[150],"network":[151],"decrease":[153],"distortion":[155],"caused":[156],"by":[157],"Finally,":[159],"an":[160],"improved":[161],"binarizer":[162],"adopted":[164],"quantize":[166],"output":[168],"encoder.":[170],"In":[171],"low":[172],"bit":[173],"rate":[174],"experiments":[177],"show":[178],"that":[179],"our":[180],"method":[181],"significantly":[182],"outperforms":[183],"JPEG":[184],"JPEG2000":[186],"better":[191],"visual":[192],"result":[193],"with":[194],"sharp":[195],"edges,":[196],"rich":[197],"textures,":[198],"fewer":[200],"artifacts.":[201]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
