乐胖代购免代理版

{"id":"https://openalex.org/W3032972997","doi":"https://doi.org/10.1109/dcc47342.2020.00009","title":"Deep Learning-Based Image Compression with Trellis Coded Quantization","display_name":"Deep Learning-Based Image Compression with Trellis Coded Quantization","publication_year":2020,"publication_date":"2020-03-01","ids":{"openalex":"https://openalex.org/W3032972997","doi":"https://doi.org/10.1109/dcc47342.2020.00009","mag":"3032972997"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/dcc47342.2020.00009","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":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2001.09417","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100649277","display_name":"Binglin Li","orcid":"https://orcid.org/0000-0003-2798-1710"},"institutions":[{"id":"https://openalex.org/I18014758","display_name":"Simon Fraser University","ror":"https://ror.org/0213rcc28","country_code":"CA","type":"funder","lineage":["https://openalex.org/I18014758"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Binglin Li","raw_affiliation_strings":["School of Engineering Science, Simon Fraser University, Burnaby, Canada"],"affiliations":[{"raw_affiliation_string":"School of Engineering Science, Simon Fraser University, Burnaby, Canada","institution_ids":["https://openalex.org/I18014758"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019919020","display_name":"Mohammad Akbari","orcid":"https://orcid.org/0000-0002-5663-3101"},"institutions":[{"id":"https://openalex.org/I18014758","display_name":"Simon Fraser University","ror":"https://ror.org/0213rcc28","country_code":"CA","type":"funder","lineage":["https://openalex.org/I18014758"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Mohammad Akbari","raw_affiliation_strings":["School of Engineering Science, Simon Fraser University, Burnaby, Canada"],"affiliations":[{"raw_affiliation_string":"School of Engineering Science, Simon Fraser University, Burnaby, Canada","institution_ids":["https://openalex.org/I18014758"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108166775","display_name":"Jie Liang","orcid":"https://orcid.org/0000-0003-3003-4343"},"institutions":[{"id":"https://openalex.org/I18014758","display_name":"Simon Fraser University","ror":"https://ror.org/0213rcc28","country_code":"CA","type":"funder","lineage":["https://openalex.org/I18014758"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Jie Liang","raw_affiliation_strings":["School of Engineering Science, Simon Fraser University, Burnaby, Canada"],"affiliations":[{"raw_affiliation_string":"School of Engineering Science, Simon Fraser University, Burnaby, Canada","institution_ids":["https://openalex.org/I18014758"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100423354","display_name":"Yang Wang","orcid":"https://orcid.org/0000-0002-8903-2388"},"institutions":[{"id":"https://openalex.org/I46247651","display_name":"University of Manitoba","ror":"https://ror.org/02gfys938","country_code":"CA","type":"funder","lineage":["https://openalex.org/I46247651"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Yang Wang","raw_affiliation_strings":["Department of Computer Science, University of Manitoba, Winnipeg, Canada"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Manitoba, Winnipeg, Canada","institution_ids":["https://openalex.org/I46247651"]}]}],"institution_assertions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.498,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.546482,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":83,"max":84},"biblio":{"volume":null,"issue":null,"first_page":"13","last_page":"22"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T10901","display_name":"Advanced Data Compression 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/T10901","display_name":"Advanced Data Compression 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/T11105","display_name":"Advanced Image Processing Techniques","score":0.9992,"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":0.9992,"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/trellis","display_name":"Trellis (graph)","score":0.5468358}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7220865},{"id":"https://openalex.org/C13481523","wikidata":"https://www.wikidata.org/wiki/Q412438","display_name":"Image compression","level":4,"score":0.6354491},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.59097767},{"id":"https://openalex.org/C28855332","wikidata":"https://www.wikidata.org/wiki/Q198099","display_name":"Quantization (signal processing)","level":2,"score":0.585991},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5803472},{"id":"https://openalex.org/C2781235587","wikidata":"https://www.wikidata.org/wiki/Q7838009","display_name":"Trellis (graph)","level":3,"score":0.5468358},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.51855546},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.45023474},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.42995802},{"id":"https://openalex.org/C78548338","wikidata":"https://www.wikidata.org/wiki/Q2493","display_name":"Data compression","level":2,"score":0.41838986},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.37447655},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.35758308},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.34987646},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.32677037},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.20008394},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","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":2,"locations":[{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/dcc47342.2020.00009","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},{"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2001.09417","pdf_url":"https://arxiv.org/pdf/2001.09417","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_indexed_in_scopus":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":["Cornell University"],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false}],"best_oa_location":{"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2001.09417","pdf_url":"https://arxiv.org/pdf/2001.09417","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_indexed_in_scopus":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":["Cornell University"],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false},"sustainable_development_goals":[],"grants":[],"datasets":[],"versions":[],"referenced_works_count":26,"referenced_works":["https://openalex.org/W2133882791","https://openalex.org/W2140196014","https://openalex.org/W2167875972","https://openalex.org/W2194775991","https://openalex.org/W2242818861","https://openalex.org/W2286454943","https://openalex.org/W2476548250","https://openalex.org/W2588610957","https://openalex.org/W2597747080","https://openalex.org/W2604392022","https://openalex.org/W2732044853","https://openalex.org/W2737258237","https://openalex.org/W2892278106","https://openalex.org/W2948654165","https://openalex.org/W2949361041","https://openalex.org/W2950237263","https://openalex.org/W2962676454","https://openalex.org/W2962790638","https://openalex.org/W2962847516","https://openalex.org/W2962891349","https://openalex.org/W2963300719","https://openalex.org/W2963966654","https://openalex.org/W2964122153","https://openalex.org/W2964164354","https://openalex.org/W4294567867","https://openalex.org/W4297659253"],"related_works":["https://openalex.org/W4378191574","https://openalex.org/W4313046148","https://openalex.org/W4243608781","https://openalex.org/W3165542721","https://openalex.org/W2751842002","https://openalex.org/W2521595930","https://openalex.org/W2161981399","https://openalex.org/W2129829718","https://openalex.org/W1939109514","https://openalex.org/W1843792225"],"abstract_inverted_index":{"Recently":[0],"many":[1],"works":[2],"attempt":[3],"to":[4,23,37,56],"develop":[5,64],"image":[6,48,67,96],"compression":[7,49,68],"models":[8],"based":[9,47,121],"on":[10,92,122],"deep":[11,45],"learning":[12,46],"architectures,":[13],"where":[14],"the":[15,24,28,84,115,129],"uniform":[16],"scalar":[17],"quantizer":[18,41],"(SQ)":[19],"is":[20,54],"commonly":[21],"applied":[22,55],"feature":[25],"maps":[26],"between":[27,117],"encoder":[29],"and":[30,77,80,98,119,127],"decoder.":[31],"In":[32],"this":[33],"paper,":[34],"we":[35],"propose":[36],"incorporate":[38],"trellis":[39],"coded":[40],"(TCQ)":[42],"into":[43],"a":[44,65],"framework.":[50],"A":[51],"soft-to-hard":[52],"strategy":[53],"allow":[57],"for":[58],"back":[59],"propagation":[60],"during":[61],"training.":[62],"We":[63,90,112],"simple":[66],"model":[69,103,126],"that":[70,101],"consists":[71],"of":[72,83,131],"three":[73],"subnetworks":[74],"(encoder,":[75],"decoder":[76],"entropy":[78],"estimation),":[79],"optimize":[81],"all":[82],"components":[85],"in":[86],"an":[87],"end-to-end":[88],"manner.":[89],"experiment":[91],"two":[93],"high":[94],"resolution":[95],"datasets":[97],"both":[99],"show":[100,114],"our":[102,123],"can":[104],"achieve":[105],"superior":[106],"performance":[107],"at":[108],"low":[109],"bit":[110],"rates.":[111],"also":[113],"comparisons":[116],"TCQ":[118],"SQ":[120],"proposed":[124],"baseline":[125],"demonstrate":[128],"advantage":[130],"TCQ.":[132]},"abstract_inverted_index_v3":null,"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W3032972997","counts_by_year":[{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":4}],"updated_date":"2025-04-19T05:53:14.138243","created_date":"2020-06-12"}