{"id":"https://openalex.org/W7135138443","doi":"https://doi.org/10.5753/jbcs.2026.5873","title":"CNNs for JPEGs: Designing Cost-Efficient Stems","display_name":"CNNs for JPEGs: Designing Cost-Efficient Stems","publication_year":2026,"publication_date":"2026-03-02","ids":{"openalex":"https://openalex.org/W7135138443","doi":"https://doi.org/10.5753/jbcs.2026.5873"},"language":"en","primary_location":{"id":"doi:10.5753/jbcs.2026.5873","is_oa":true,"landing_page_url":"https://doi.org/10.5753/jbcs.2026.5873","pdf_url":"https://journals-sol.sbc.org.br/index.php/jbcs/article/download/5873/3825","source":{"id":"https://openalex.org/S69801987","display_name":"Journal of the Brazilian Computer Society","issn_l":"0104-6500","issn":["0104-6500","1678-4804"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of the Brazilian Computer Society","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://journals-sol.sbc.org.br/index.php/jbcs/article/download/5873/3825","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5035632220","display_name":"Samuel Felipe dos Santos","orcid":"https://orcid.org/0000-0001-6061-5582"},"institutions":[{"id":"https://openalex.org/I177909021","display_name":"Universidade Federal de S\u00e3o Carlos","ror":"https://ror.org/00qdc6m37","country_code":"BR","type":"education","lineage":["https://openalex.org/I177909021"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Samuel Felipe Dos Santos","raw_affiliation_strings":["Federal University of S\u00e3o Carlos"],"raw_orcid":"https://orcid.org/0000-0001-6061-5582","affiliations":[{"raw_affiliation_string":"Federal University of S\u00e3o Carlos","institution_ids":["https://openalex.org/I177909021"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128811452","display_name":"Nicu Sebe","orcid":null},"institutions":[{"id":"https://openalex.org/I193223587","display_name":"University of Trento","ror":"https://ror.org/05trd4x28","country_code":"IT","type":"education","lineage":["https://openalex.org/I193223587"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Nicu Sebe","raw_affiliation_strings":["University of Trento"],"raw_orcid":"https://orcid.org/0000-0002-6597-7248","affiliations":[{"raw_affiliation_string":"University of Trento","institution_ids":["https://openalex.org/I193223587"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5107957281","display_name":"Jurandy Almeida","orcid":null},"institutions":[{"id":"https://openalex.org/I177909021","display_name":"Universidade Federal de S\u00e3o Carlos","ror":"https://ror.org/00qdc6m37","country_code":"BR","type":"education","lineage":["https://openalex.org/I177909021"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Jurandy Almeida","raw_affiliation_strings":["Federal University of S\u00e3o Carlos"],"raw_orcid":"https://orcid.org/0000-0002-4998-6996","affiliations":[{"raw_affiliation_string":"Federal University of S\u00e3o Carlos","institution_ids":["https://openalex.org/I177909021"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1390,"currency":"USD","value_usd":1390},"apc_paid":{"value":1390,"currency":"USD","value_usd":1390},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.28448617,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"32","issue":"1","first_page":"201","last_page":"215"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.6740000247955322,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.6740000247955322,"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/T12357","display_name":"Digital Media Forensic Detection","score":0.045499999076128006,"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":0.0348999984562397,"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/decoding-methods","display_name":"Decoding methods","score":0.628600001335144},{"id":"https://openalex.org/keywords/computational-complexity-theory","display_name":"Computational complexity theory","score":0.6013000011444092},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5608999729156494},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4745999872684479},{"id":"https://openalex.org/keywords/jpeg","display_name":"JPEG","score":0.46810001134872437},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.4648999869823456},{"id":"https://openalex.org/keywords/bottleneck","display_name":"Bottleneck","score":0.45750001072883606},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.43130001425743103},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.4244999885559082},{"id":"https://openalex.org/keywords/codec","display_name":"Codec","score":0.3707999885082245}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.876800000667572},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.628600001335144},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.6013000011444092},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5842999815940857},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5608999729156494},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4745999872684479},{"id":"https://openalex.org/C198751489","wikidata":"https://www.wikidata.org/wiki/Q2195","display_name":"JPEG","level":3,"score":0.46810001134872437},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.4648999869823456},{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.45750001072883606},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.43130001425743103},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.4244999885559082},{"id":"https://openalex.org/C161765866","wikidata":"https://www.wikidata.org/wiki/Q184748","display_name":"Codec","level":2,"score":0.3707999885082245},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.36329999566078186},{"id":"https://openalex.org/C127964446","wikidata":"https://www.wikidata.org/wiki/Q1092142","display_name":"Computational resource","level":3,"score":0.3571000099182129},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.3522000014781952},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.35040000081062317},{"id":"https://openalex.org/C66024118","wikidata":"https://www.wikidata.org/wiki/Q1122506","display_name":"Computational model","level":2,"score":0.3472999930381775},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.33820000290870667},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.33709999918937683},{"id":"https://openalex.org/C13481523","wikidata":"https://www.wikidata.org/wiki/Q412438","display_name":"Image compression","level":4,"score":0.3278000056743622},{"id":"https://openalex.org/C78548338","wikidata":"https://www.wikidata.org/wiki/Q2493","display_name":"Data compression","level":2,"score":0.3197000026702881},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.3122999966144562},{"id":"https://openalex.org/C2780490138","wikidata":"https://www.wikidata.org/wiki/Q7079636","display_name":"Offline learning","level":3,"score":0.30869999527931213},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3052000105381012},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.303600013256073},{"id":"https://openalex.org/C19118579","wikidata":"https://www.wikidata.org/wiki/Q786423","display_name":"Frequency domain","level":2,"score":0.28839999437332153},{"id":"https://openalex.org/C761482","wikidata":"https://www.wikidata.org/wiki/Q118093","display_name":"Transmission (telecommunications)","level":2,"score":0.28110000491142273},{"id":"https://openalex.org/C116409475","wikidata":"https://www.wikidata.org/wiki/Q1385056","display_name":"External Data Representation","level":2,"score":0.2761000096797943},{"id":"https://openalex.org/C149810388","wikidata":"https://www.wikidata.org/wiki/Q5374873","display_name":"Emulation","level":2,"score":0.26260000467300415},{"id":"https://openalex.org/C3261483","wikidata":"https://www.wikidata.org/wiki/Q119565","display_name":"Frame rate","level":2,"score":0.26249998807907104},{"id":"https://openalex.org/C60008888","wikidata":"https://www.wikidata.org/wiki/Q6031013","display_name":"Information bottleneck method","level":3,"score":0.26190000772476196},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2565999925136566},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.2563999891281128},{"id":"https://openalex.org/C2781357197","wikidata":"https://www.wikidata.org/wiki/Q5757597","display_name":"High memory","level":2,"score":0.2540999948978424},{"id":"https://openalex.org/C194739806","wikidata":"https://www.wikidata.org/wiki/Q66221","display_name":"Computer data storage","level":2,"score":0.25110000371932983}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.5753/jbcs.2026.5873","is_oa":true,"landing_page_url":"https://doi.org/10.5753/jbcs.2026.5873","pdf_url":"https://journals-sol.sbc.org.br/index.php/jbcs/article/download/5873/3825","source":{"id":"https://openalex.org/S69801987","display_name":"Journal of the Brazilian Computer Society","issn_l":"0104-6500","issn":["0104-6500","1678-4804"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of the Brazilian Computer Society","raw_type":"journal-article"},{"id":"pmh:oai:iris.unitn.it:11572/481490","is_oa":true,"landing_page_url":"https://journals-sol.sbc.org.br/index.php/jbcs/article/view/5873","pdf_url":null,"source":{"id":"https://openalex.org/S4306401913","display_name":"Institutional Research Information System (Universit\u00e0 degli Studi di Trento)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I193223587","host_organization_name":"University of Trento","host_organization_lineage":["https://openalex.org/I193223587"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"doi:10.5753/jbcs.2026.5873","is_oa":true,"landing_page_url":"https://doi.org/10.5753/jbcs.2026.5873","pdf_url":"https://journals-sol.sbc.org.br/index.php/jbcs/article/download/5873/3825","source":{"id":"https://openalex.org/S69801987","display_name":"Journal of the Brazilian Computer Society","issn_l":"0104-6500","issn":["0104-6500","1678-4804"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of the Brazilian Computer Society","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.48989343643188477,"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure"}],"awards":[{"id":"https://openalex.org/G116629194","display_name":null,"funder_award_id":"88881","funder_id":"https://openalex.org/F4320321091","funder_display_name":"Coordena\u00e7\u00e3o de Aperfei\u00e7oamento de Pessoal de N\u00edvel Superior"},{"id":"https://openalex.org/G1412218740","display_name":null,"funder_award_id":"2017/ 25908-6","funder_id":"https://openalex.org/F4320320997","funder_display_name":"Funda\u00e7\u00e3o de Amparo \u00e0 Pesquisa do Estado de S\u00e3o Paulo"},{"id":"https://openalex.org/G3753736230","display_name":null,"funder_award_id":"315220/2023-6","funder_id":"https://openalex.org/F4320321091","funder_display_name":"Coordena\u00e7\u00e3o de Aperfei\u00e7oamento de Pessoal de N\u00edvel Superior"},{"id":"https://openalex.org/G5471421749","display_name":null,"funder_award_id":"420442/2023-5","funder_id":"https://openalex.org/F4320321091","funder_display_name":"Coordena\u00e7\u00e3o de Aperfei\u00e7oamento de Pessoal de N\u00edvel Superior"},{"id":"https://openalex.org/G6815844370","display_name":null,"funder_award_id":"88881","funder_id":"https://openalex.org/F4320322025","funder_display_name":"Conselho Nacional de Desenvolvimento Cient\u00edfico e Tecnol\u00f3gico"}],"funders":[{"id":"https://openalex.org/F4320308943","display_name":"Microsoft Research","ror":"https://ror.org/00d0nc645"},{"id":"https://openalex.org/F4320320997","display_name":"Funda\u00e7\u00e3o de Amparo \u00e0 Pesquisa do Estado de S\u00e3o Paulo","ror":"https://ror.org/02ddkpn78"},{"id":"https://openalex.org/F4320321091","display_name":"Coordena\u00e7\u00e3o de Aperfei\u00e7oamento de Pessoal de N\u00edvel Superior","ror":"https://ror.org/00x0ma614"},{"id":"https://openalex.org/F4320322025","display_name":"Conselho Nacional de Desenvolvimento Cient\u00edfico e Tecnol\u00f3gico","ror":"https://ror.org/03swz6y49"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7135138443.pdf","grobid_xml":"https://content.openalex.org/works/W7135138443.grobid-xml"},"referenced_works_count":46,"referenced_works":["https://openalex.org/W1902237438","https://openalex.org/W2043331342","https://openalex.org/W2117539524","https://openalex.org/W2193145675","https://openalex.org/W2194775991","https://openalex.org/W2531409750","https://openalex.org/W2620676860","https://openalex.org/W2778053709","https://openalex.org/W2884675507","https://openalex.org/W2900401464","https://openalex.org/W2935860405","https://openalex.org/W2963512705","https://openalex.org/W2963524571","https://openalex.org/W2974437627","https://openalex.org/W2987748894","https://openalex.org/W2989808579","https://openalex.org/W2992813059","https://openalex.org/W2995170449","https://openalex.org/W2998922690","https://openalex.org/W3034771037","https://openalex.org/W3089411267","https://openalex.org/W3107289539","https://openalex.org/W3109737331","https://openalex.org/W3163825518","https://openalex.org/W3182371322","https://openalex.org/W3207810281","https://openalex.org/W3210165700","https://openalex.org/W4206004830","https://openalex.org/W4214666412","https://openalex.org/W4231030295","https://openalex.org/W4248863248","https://openalex.org/W4249246468","https://openalex.org/W4285537257","https://openalex.org/W4296131359","https://openalex.org/W4310147199","https://openalex.org/W4319602321","https://openalex.org/W4320015860","https://openalex.org/W4367322714","https://openalex.org/W4386071602","https://openalex.org/W4387910417","https://openalex.org/W4390872354","https://openalex.org/W4391070153","https://openalex.org/W4391569088","https://openalex.org/W4396243191","https://openalex.org/W4404954860","https://openalex.org/W4408406616"],"related_works":[],"abstract_inverted_index":{"Convolutional":[0],"neural":[1],"networks":[2],"(CNNs)":[3],"have":[4,114],"achieved":[5],"astonishing":[6],"advances":[7],"over":[8],"the":[9,13,28,46,49,111,130,159,167,171,179,187,194,198,210,213,217,235,240,287],"past":[10],"decade,":[11],"pushing":[12],"state-of-the-art":[14],"in":[15,41,118,246,260,272,280],"several":[16],"computer":[17],"vision":[18],"tasks.":[19],"CNNs":[20],"are":[21,98],"capable":[22,106],"of":[23,27,44,107,129,158,162,173,234,264,303],"learning":[24,104,108],"robust":[25],"representations":[26],"data":[29,37],"directly":[30,109],"from":[31,110],"RGB":[32],"pixels.":[33],"However,":[34],"most":[35,50],"image":[36],"is":[38,48,75],"usually":[39,123],"available":[40],"compressed":[42,112,195],"format,":[43],"which":[45],"JPEG":[47],"widely":[51],"used":[52],"due":[53],"to":[54,142,146,191,208,212,257,269,282,291],"transmission":[55],"and":[56,72,138,175,252,301],"storage":[57],"purposes.":[58],"For":[59,100],"this":[60,101,151],"motive,":[61],"a":[62,68,81,125,135,261],"preliminary":[63],"decoding":[64,78,174,204],"process":[65],"that":[66,183,215,249],"has":[67],"high":[69],"computational":[70,88,160,189,218,273,299],"load":[71],"memory":[73],"usage":[74],"demanded.":[76],"Image":[77],"can":[79,230],"be":[80,258],"performance":[82],"bottleneck":[83],"for":[84,166,193],"devices":[85],"with":[86,148,222,294],"limited":[87],"resources,":[89],"such":[90],"as":[91],"embedded":[92],"devices,":[93],"even":[94],"when":[95],"hardware":[96],"accelerators":[97],"used.":[99],"reason,":[102],"deep":[103,163,255],"methods":[105,122],"domain":[113,127],"been":[115],"gaining":[116],"attention":[117],"recent":[119],"years.":[120],"These":[121],"extract":[124],"frequency":[126,168],"representation":[128],"image,":[131],"like":[132],"DCT,":[133],"by":[134,202,238],"partial":[136],"decoding,":[137],"then":[139],"make":[140],"adaptation":[141],"typical":[143],"CNN":[144],"architectures":[145],"work":[147,185],"it.":[149],"In":[150],"paper,":[152],"we":[153,229],"perform":[154],"an":[155],"in-depth":[156],"study":[157],"cost":[161,172,300],"models":[164,248,256,293],"designed":[165,224],"domain,":[169],"evaluating":[170],"passing":[176],"images":[177],"through":[178],"network.":[180],"We":[181,206,266,284],"notice":[182],"previous":[184],"increased":[186],"model's":[188],"complexity":[190,274],"accommodate":[192],"images,":[196],"nullifying":[197],"speed":[199],"up":[200,268,281],"gained":[201],"not":[203],"images.":[205],"propose":[207,286],"remove":[209],"changes":[211],"model":[214],"increase":[216],"cost,":[219],"replacing":[220],"it":[221],"our":[223],"lightweight":[225],"stems.":[226],"This":[227],"way,":[228],"take":[231],"full":[232],"advantage":[233],"speed-up":[236],"obtained":[237],"avoiding":[239],"decoding.":[241],"Our":[242],"strategies":[243],"were":[244],"successful":[245],"generating":[247],"balance":[250],"efficiency":[251],"effectiveness,":[253],"allowing":[254],"deployed":[259],"wider":[262],"array":[263],"devices.":[265],"achieve":[267],"25.91%":[270],"reduction":[271],"(FLOPs),":[275],"while":[276],"only":[277],"decreasing":[278],"accuracy":[279],"2.97%.":[283],"also":[285],"efficiency-effectiveness":[288],"score":[289],"SE":[290],"highlight":[292],"favorable":[295],"trade-offs":[296],"between":[297],"accuracy,":[298],"number":[302],"parameters.":[304]},"counts_by_year":[],"updated_date":"2026-08-06T08:24:18.245995","created_date":"2026-03-13T00:00:00"}
