{"id":"https://openalex.org/W2890991392","doi":"https://doi.org/10.1109/pcs.2018.8456311","title":"CNN-based Prediction for Lossless Coding of Photographic Images","display_name":"CNN-based Prediction for Lossless Coding of Photographic Images","publication_year":2018,"publication_date":"2018-06-01","ids":{"openalex":"https://openalex.org/W2890991392","doi":"https://doi.org/10.1109/pcs.2018.8456311","mag":"2890991392"},"language":"en","primary_location":{"id":"doi:10.1109/pcs.2018.8456311","is_oa":false,"landing_page_url":"https://doi.org/10.1109/pcs.2018.8456311","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 Picture Coding Symposium (PCS)","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/A5060196436","display_name":"Ionut Schiopu","orcid":"https://orcid.org/0000-0003-2202-1163"},"institutions":[{"id":"https://openalex.org/I13469542","display_name":"Vrije Universiteit Brussel","ror":"https://ror.org/006e5kg04","country_code":"BE","type":"education","lineage":["https://openalex.org/I13469542"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"Ionut Schiopu","raw_affiliation_strings":["Department of Electronics and Informatics (ETRO), Vrije Universiteit Brussel (VUB), Brussels, Belgium"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electronics and Informatics (ETRO), Vrije Universiteit Brussel (VUB), Brussels, Belgium","institution_ids":["https://openalex.org/I13469542"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034675261","display_name":"Yu Liu","orcid":"https://orcid.org/0000-0002-5949-6587"},"institutions":[{"id":"https://openalex.org/I13469542","display_name":"Vrije Universiteit Brussel","ror":"https://ror.org/006e5kg04","country_code":"BE","type":"education","lineage":["https://openalex.org/I13469542"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"Yu Liu","raw_affiliation_strings":["Department of Electronics and Informatics (ETRO), Vrije Universiteit Brussel (VUB), Brussels, Belgium"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electronics and Informatics (ETRO), Vrije Universiteit Brussel (VUB), Brussels, Belgium","institution_ids":["https://openalex.org/I13469542"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5088598176","display_name":"Adrian Munteanu","orcid":"https://orcid.org/0000-0001-7290-0428"},"institutions":[{"id":"https://openalex.org/I13469542","display_name":"Vrije Universiteit Brussel","ror":"https://ror.org/006e5kg04","country_code":"BE","type":"education","lineage":["https://openalex.org/I13469542"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"Adrian Munteanu","raw_affiliation_strings":["Department of Electronics and Informatics (ETRO), Vrije Universiteit Brussel (VUB), Brussels, Belgium"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electronics and Informatics (ETRO), Vrije Universiteit Brussel (VUB), Brussels, Belgium","institution_ids":["https://openalex.org/I13469542"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.59,"has_fulltext":false,"cited_by_count":20,"citation_normalized_percentile":{"value":0.88052624,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"16","last_page":"20"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10901","display_name":"Advanced Data Compression 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/T10901","display_name":"Advanced Data Compression 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/T11105","display_name":"Advanced Image Processing 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"}},{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9991999864578247,"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/computer-science","display_name":"Computer science","score":0.841937243938446},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7267262935638428},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7132332921028137},{"id":"https://openalex.org/keywords/lossless-compression","display_name":"Lossless compression","score":0.5896501541137695},{"id":"https://openalex.org/keywords/codec","display_name":"Codec","score":0.578551173210144},{"id":"https://openalex.org/keywords/entropy-encoding","display_name":"Entropy encoding","score":0.5598597526550293},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.4558807611465454},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.44849610328674316},{"id":"https://openalex.org/keywords/data-compression","display_name":"Data compression","score":0.44428691267967224},{"id":"https://openalex.org/keywords/coding","display_name":"Coding (social sciences)","score":0.4197064936161041},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4140982925891876},{"id":"https://openalex.org/keywords/image-compression","display_name":"Image compression","score":0.4135923385620117},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.36728912591934204},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.27770745754241943},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.22816389799118042},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.07761338353157043}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.841937243938446},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7267262935638428},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7132332921028137},{"id":"https://openalex.org/C81081738","wikidata":"https://www.wikidata.org/wiki/Q55542","display_name":"Lossless compression","level":3,"score":0.5896501541137695},{"id":"https://openalex.org/C161765866","wikidata":"https://www.wikidata.org/wiki/Q184748","display_name":"Codec","level":2,"score":0.578551173210144},{"id":"https://openalex.org/C1769480","wikidata":"https://www.wikidata.org/wiki/Q1345239","display_name":"Entropy encoding","level":3,"score":0.5598597526550293},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.4558807611465454},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.44849610328674316},{"id":"https://openalex.org/C78548338","wikidata":"https://www.wikidata.org/wiki/Q2493","display_name":"Data compression","level":2,"score":0.44428691267967224},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.4197064936161041},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4140982925891876},{"id":"https://openalex.org/C13481523","wikidata":"https://www.wikidata.org/wiki/Q412438","display_name":"Image compression","level":4,"score":0.4135923385620117},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.36728912591934204},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.27770745754241943},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.22816389799118042},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.07761338353157043},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"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/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/pcs.2018.8456311","is_oa":false,"landing_page_url":"https://doi.org/10.1109/pcs.2018.8456311","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 Picture Coding Symposium (PCS)","raw_type":"proceedings-article"},{"id":"pmh:oai:vubissmart:VUBISSMART:2000:113852","is_oa":false,"landing_page_url":"https://biblio.vub.ac.be/vubir/cnnbased-prediction-for-lossless-coding-of-photographic-images(47c76eae-cff5-496f-b52f-bc376070f74c).html","pdf_url":null,"source":{"id":"https://openalex.org/S4306402573","display_name":"VUBIR (Vrije Universiteit Brussel)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I13469542","host_organization_name":"Vrije Universiteit Brussel","host_organization_lineage":["https://openalex.org/I13469542"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320322852","display_name":"Innoviris","ror":"https://ror.org/04af9zr29"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1533861849","https://openalex.org/W1663973292","https://openalex.org/W1665214252","https://openalex.org/W1677182931","https://openalex.org/W2047028564","https://openalex.org/W2096445898","https://openalex.org/W2147800946","https://openalex.org/W2153638435","https://openalex.org/W2163605009","https://openalex.org/W2343938449","https://openalex.org/W2963147844","https://openalex.org/W2963149687","https://openalex.org/W2964121744","https://openalex.org/W4212863985","https://openalex.org/W4234173777","https://openalex.org/W6631190155","https://openalex.org/W6631943919","https://openalex.org/W6637242042","https://openalex.org/W6684191040","https://openalex.org/W6704734575"],"related_works":["https://openalex.org/W56034600","https://openalex.org/W2162059757","https://openalex.org/W2038945488","https://openalex.org/W2145658374","https://openalex.org/W1901175001","https://openalex.org/W2504835222","https://openalex.org/W4308236560","https://openalex.org/W2161453113","https://openalex.org/W2139274214","https://openalex.org/W2160328073"],"abstract_inverted_index":{"The":[0,32,59,82,92],"paper":[1,112],"proposes":[2],"a":[3,29,51,78,88,96],"novel":[4],"prediction":[5,26,35,65,83,102,119],"paradigm":[6,66],"in":[7,43,50,120,132],"image":[8,45,121],"coding":[9,133],"based":[10,27],"on":[11,28,39],"Convolutional":[12],"Neural":[13],"Networks":[14],"(CNN).":[15],"A":[16],"deep":[17],"neural":[18],"network":[19],"is":[20,37,48,75,113],"designed":[21],"to":[22,105,116],"provide":[23],"accurate":[24],"pixel-wise":[25],"causal":[30],"neighbourhood.":[31],"proposed":[33,63,101],"CNN":[34],"method":[36],"trained":[38],"the":[40,44,62,72,100,111,114,125],"high-activity":[41],"areas":[42],"and":[46,123],"it":[47],"incorporated":[49],"lossless":[52],"compression":[53],"system":[54,60],"for":[55,99],"high-resolution":[56],"photographic":[57],"images.":[58],"uses":[61],"CNN-based":[64,118],"as":[67,69],"well":[68],"LOCO-I,":[70],"whereby":[71],"predictor":[73],"selection":[74],"performed":[76],"using":[77,87],"local":[79],"entropy-based":[80],"descriptor.":[81],"errors":[84],"are":[85],"encoded":[86],"CALIC-based":[89],"reference":[90],"codec.":[91],"experimental":[93],"results":[94],"show":[95],"good":[97],"performance":[98],"scheme":[103],"compared":[104],"state-of-the-art":[106],"predictors.":[107],"To":[108],"our":[109],"knowledge,":[110],"first":[115],"introduce":[117],"coding,":[122],"demonstrates":[124],"potential":[126],"offered":[127],"by":[128],"machine":[129],"learning":[130],"methods":[131],"applications.":[134]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":6},{"year":2019,"cited_by_count":6},{"year":2012,"cited_by_count":1}],"updated_date":"2026-06-21T07:57:09.225873","created_date":"2025-10-10T00:00:00"}
