{"id":"https://openalex.org/W4386362365","doi":"https://doi.org/10.1109/civemsa57781.2023.10230904","title":"Tree-based Optimization for Image-to-Image Translation with Imbalanced Datasets on the Edge","display_name":"Tree-based Optimization for Image-to-Image Translation with Imbalanced Datasets on the Edge","publication_year":2023,"publication_date":"2023-06-12","ids":{"openalex":"https://openalex.org/W4386362365","doi":"https://doi.org/10.1109/civemsa57781.2023.10230904"},"language":"en","primary_location":{"id":"doi:10.1109/civemsa57781.2023.10230904","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/civemsa57781.2023.10230904","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://air.unimi.it/bitstream/2434/967204/2/civemsa23a.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5067609101","display_name":"Pasquale Coscia","orcid":"https://orcid.org/0000-0003-4726-3409"},"institutions":[{"id":"https://openalex.org/I189158943","display_name":"University of Milan","ror":"https://ror.org/00wjc7c48","country_code":"IT","type":"education","lineage":["https://openalex.org/I189158943"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Pasquale Coscia","raw_affiliation_strings":["Universit&#x00E0; degli Studi di Milano,Department of Computer Science,Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universit&#x00E0; degli Studi di Milano,Department of Computer Science,Italy","institution_ids":["https://openalex.org/I189158943"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031772222","display_name":"Angelo Genovese","orcid":"https://orcid.org/0000-0002-3683-4723"},"institutions":[{"id":"https://openalex.org/I189158943","display_name":"University of Milan","ror":"https://ror.org/00wjc7c48","country_code":"IT","type":"education","lineage":["https://openalex.org/I189158943"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Angelo Genovese","raw_affiliation_strings":["Universit&#x00E0; degli Studi di Milano,Department of Computer Science,Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universit&#x00E0; degli Studi di Milano,Department of Computer Science,Italy","institution_ids":["https://openalex.org/I189158943"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009147954","display_name":"Vincenzo Piuri","orcid":"https://orcid.org/0000-0003-3178-8198"},"institutions":[{"id":"https://openalex.org/I189158943","display_name":"University of Milan","ror":"https://ror.org/00wjc7c48","country_code":"IT","type":"education","lineage":["https://openalex.org/I189158943"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Vincenzo Piuri","raw_affiliation_strings":["Universit&#x00E0; degli Studi di Milano,Department of Computer Science,Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universit&#x00E0; degli Studi di Milano,Department of Computer Science,Italy","institution_ids":["https://openalex.org/I189158943"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036892535","display_name":"Francesco Rundo","orcid":"https://orcid.org/0000-0003-1766-3065"},"institutions":[{"id":"https://openalex.org/I4210154781","display_name":"STMicroelectronics (Italy)","ror":"https://ror.org/053bqv655","country_code":"IT","type":"company","lineage":["https://openalex.org/I131827901","https://openalex.org/I4210154781"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Francesco Rundo","raw_affiliation_strings":["STMicroelectronics, ADG Central R&#x0026;D,Catania,Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"STMicroelectronics, ADG Central R&#x0026;D,Catania,Italy","institution_ids":["https://openalex.org/I4210154781"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5004969615","display_name":"Fabio Scotti","orcid":"https://orcid.org/0000-0002-4277-3701"},"institutions":[{"id":"https://openalex.org/I189158943","display_name":"University of Milan","ror":"https://ror.org/00wjc7c48","country_code":"IT","type":"education","lineage":["https://openalex.org/I189158943"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Fabio Scotti","raw_affiliation_strings":["Universit&#x00E0; degli Studi di Milano,Department of Computer Science,Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universit&#x00E0; degli Studi di Milano,Department of Computer Science,Italy","institution_ids":["https://openalex.org/I189158943"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9994000196456909,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9994000196456909,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9980000257492065,"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":0.994700014591217,"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/overfitting","display_name":"Overfitting","score":0.9068295955657959},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7528058290481567},{"id":"https://openalex.org/keywords/image-translation","display_name":"Image translation","score":0.7142056226730347},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.6606724262237549},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.6498351693153381},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.6359933018684387},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.571171760559082},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.5409821271896362},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5037218928337097},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.4942922592163086},{"id":"https://openalex.org/keywords/translation","display_name":"Translation (biology)","score":0.46280235052108765},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.44815126061439514},{"id":"https://openalex.org/keywords/image-quality","display_name":"Image quality","score":0.41443705558776855},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.35711878538131714},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3284265697002411},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.15419209003448486},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.13610413670539856}],"concepts":[{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.9068295955657959},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7528058290481567},{"id":"https://openalex.org/C2779757391","wikidata":"https://www.wikidata.org/wiki/Q6002292","display_name":"Image translation","level":3,"score":0.7142056226730347},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.6606724262237549},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.6498351693153381},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.6359933018684387},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.571171760559082},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.5409821271896362},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5037218928337097},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.4942922592163086},{"id":"https://openalex.org/C149364088","wikidata":"https://www.wikidata.org/wiki/Q185917","display_name":"Translation (biology)","level":4,"score":0.46280235052108765},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.44815126061439514},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.41443705558776855},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.35711878538131714},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3284265697002411},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.15419209003448486},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.13610413670539856},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C105580179","wikidata":"https://www.wikidata.org/wiki/Q188928","display_name":"Messenger RNA","level":3,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/civemsa57781.2023.10230904","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/civemsa57781.2023.10230904","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA)","raw_type":"proceedings-article"},{"id":"pmh:oai:air.unimi.it:2434/967204","is_oa":true,"landing_page_url":"https://hdl.handle.net/2434/967204","pdf_url":"https://air.unimi.it/bitstream/2434/967204/2/civemsa23a.pdf","source":{"id":"https://openalex.org/S4306400516","display_name":"Archivio Istituzionale della Ricerca (Universita Degli Studi Di Milano)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I189158943","host_organization_name":"University of Milan","host_organization_lineage":["https://openalex.org/I189158943"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/bookPart"},{"id":"pmh:oai:zenodo.org:10498292","is_oa":true,"landing_page_url":"https://doi.org/10.1109/CIVEMSA57781.2023.10230904","pdf_url":null,"source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"CIVEMSA, IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications, Virtual, 12 June 2023","raw_type":"info:eu-repo/semantics/conferenceProceedings"}],"best_oa_location":{"id":"pmh:oai:air.unimi.it:2434/967204","is_oa":true,"landing_page_url":"https://hdl.handle.net/2434/967204","pdf_url":"https://air.unimi.it/bitstream/2434/967204/2/civemsa23a.pdf","source":{"id":"https://openalex.org/S4306400516","display_name":"Archivio Istituzionale della Ricerca (Universita Degli Studi Di Milano)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I189158943","host_organization_name":"University of Milan","host_organization_lineage":["https://openalex.org/I189158943"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/bookPart"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G507880695","display_name":null,"funder_award_id":"PE00000014","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"},{"id":"https://openalex.org/G6801139879","display_name":"Edge AI Technologies for Optimised Performance Embedded Processing","funder_award_id":"101097300","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"}],"funders":[{"id":"https://openalex.org/F4320320300","display_name":"European Commission","ror":"https://ror.org/00k4n6c32"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4386362365.pdf","grobid_xml":"https://content.openalex.org/works/W4386362365.grobid-xml"},"referenced_works_count":43,"referenced_works":["https://openalex.org/W2917767146","https://openalex.org/W2953235111","https://openalex.org/W2960833983","https://openalex.org/W2962770929","https://openalex.org/W2962785568","https://openalex.org/W2962793481","https://openalex.org/W2962947361","https://openalex.org/W2963073614","https://openalex.org/W2963767194","https://openalex.org/W2963800363","https://openalex.org/W2970821029","https://openalex.org/W2982138396","https://openalex.org/W2991907795","https://openalex.org/W2998218113","https://openalex.org/W3008814843","https://openalex.org/W3013557734","https://openalex.org/W3034600949","https://openalex.org/W3034720584","https://openalex.org/W3034723751","https://openalex.org/W3091611536","https://openalex.org/W3107096356","https://openalex.org/W3108316907","https://openalex.org/W3174417809","https://openalex.org/W3177008256","https://openalex.org/W3201409833","https://openalex.org/W3204937802","https://openalex.org/W4221155125","https://openalex.org/W4225603038","https://openalex.org/W4281718656","https://openalex.org/W4312271719","https://openalex.org/W4312894955","https://openalex.org/W4319300865","https://openalex.org/W6734074887","https://openalex.org/W6747400857","https://openalex.org/W6753770798","https://openalex.org/W6765779288","https://openalex.org/W6767032739","https://openalex.org/W6773754115","https://openalex.org/W6779093361","https://openalex.org/W6780903180","https://openalex.org/W6810127701","https://openalex.org/W6810454109","https://openalex.org/W6838629043"],"related_works":["https://openalex.org/W4288069866","https://openalex.org/W4389232935","https://openalex.org/W3155045749","https://openalex.org/W2936127876","https://openalex.org/W4387421677","https://openalex.org/W4213477128","https://openalex.org/W2957407072","https://openalex.org/W4312511225","https://openalex.org/W4281776416","https://openalex.org/W3094011899"],"abstract_inverted_index":{"Image-to-image":[0],"(I2I)":[1],"translation":[2,159],"models":[3,125],"typically":[4],"refer":[5],"to":[6,13,22,63,68,73,81,104,198],"a":[7,19,23,99,151,163,186],"class":[8],"of":[9,43,85,107,110,119,143],"adversarial":[10],"architectures":[11,199],"aiming":[12],"transfer":[14],"an":[15],"image":[16,29,175],"content":[17],"from":[18],"source":[20],"domain":[21],"target":[24],"domain.":[25,92],"To":[26,93,146],"increase":[27],"the":[28,51,89,108,141],"quality,":[30],"data":[31],"augmentation":[32],"techniques":[33],"or":[34,67,76],"collecting":[35],"new":[36,65],"samples":[37],"represent":[38],"valid":[39],"options":[40],"yet":[41],"lack":[42],"diversity":[44],"and":[45,87,101,114,165,177,192],"overfitting":[46],"may":[47],"negatively":[48],"impact":[49,188],"on":[50,189,201],"final":[52],"results.":[53],"In":[54],"this":[55,147,172],"regard,":[56],"several":[57],"practical":[58],"scenarios":[59],"do":[60],"not":[61],"permit":[62],"include":[64],"samples,":[66],"employ":[69],"powerful":[70],"hardware,":[71],"due":[72],"privacy":[74],"policies":[75],"insufficient":[77],"financial":[78],"resources,":[79],"leading":[80],"use":[82],"imbalanced":[83],"sets":[84],"images":[86],"favoring":[88],"more":[90,166],"populated":[91],"overcome":[94],"these":[95],"issues,":[96],"we":[97,149],"propose":[98],"simple":[100],"effective":[102],"procedure":[103,184],"take":[105],"advantage":[106],"combination":[109],"critical":[111],"learning":[112,183],"parameters":[113],"demonstrate":[115,170],"that":[116,161,171,180],"averaging":[117],"weights":[118],"multiple":[120,155],"pre-trained":[121],"<tex":[122,156],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[123,157],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">$\\mathrm{I}2\\mathrm{I}$</tex>":[124,158],"is":[126],"beneficial":[127,187],"for":[128,136],"increasing":[129],"model":[130],"performance,":[131],"which":[132],"can":[133,194],"be":[134,195],"optimized":[135],"edge":[137,190],"computing":[138],"without":[139],"hurting":[140],"quality":[142,176],"synthesized":[144],"images.":[145],"end,":[148],"define":[150],"tree-based":[152],"structure,":[153],"including":[154],"models,":[160],"outputs":[162],"single":[164],"reliable":[167],"network.":[168],"We":[169],"strategy":[173],"increases":[174],"also":[178],"show":[179],"our":[181],"binary-tree":[182],"has":[185],"devices,":[191],"it":[193],"easily":[196],"applied":[197],"trained":[200],"different":[202],"domains.":[203]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}