{"id":"https://openalex.org/W7127339785","doi":"https://doi.org/10.1109/rivf68649.2025.11365142","title":"DEGA: Dynamic Entropy Guided Adaptation","display_name":"DEGA: Dynamic Entropy Guided Adaptation","publication_year":2025,"publication_date":"2025-12-18","ids":{"openalex":"https://openalex.org/W7127339785","doi":"https://doi.org/10.1109/rivf68649.2025.11365142"},"language":null,"primary_location":{"id":"doi:10.1109/rivf68649.2025.11365142","is_oa":false,"landing_page_url":"https://doi.org/10.1109/rivf68649.2025.11365142","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 RIVF International Conference on Computing and Communication Technologies (RIVF)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5124919140","display_name":"Minh-Loi Duong","orcid":null},"institutions":[{"id":"https://openalex.org/I23582244","display_name":"Ho Chi Minh City University of Science","ror":"https://ror.org/05jfbgm49","country_code":"VN","type":"education","lineage":["https://openalex.org/I123565023","https://openalex.org/I23582244"]}],"countries":["VN"],"is_corresponding":false,"raw_author_name":"Minh-Loi Duong","raw_affiliation_strings":["University of Science, VNU-HCM,Faculty of Information Technology,Ho Chi Minh City,Viet Nam"],"raw_orcid":"https://orcid.org/0009-0002-5757-784X","affiliations":[{"raw_affiliation_string":"University of Science, VNU-HCM,Faculty of Information Technology,Ho Chi Minh City,Viet Nam","institution_ids":["https://openalex.org/I23582244"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052866842","display_name":"Minh-Duc Huynh","orcid":null},"institutions":[{"id":"https://openalex.org/I23582244","display_name":"Ho Chi Minh City University of Science","ror":"https://ror.org/05jfbgm49","country_code":"VN","type":"education","lineage":["https://openalex.org/I123565023","https://openalex.org/I23582244"]}],"countries":["VN"],"is_corresponding":false,"raw_author_name":"Minh-Duc Huynh","raw_affiliation_strings":["University of Science, VNU-HCM,Faculty of Information Technology,Ho Chi Minh City,Viet Nam"],"raw_orcid":"https://orcid.org/0009-0008-8134-3115","affiliations":[{"raw_affiliation_string":"University of Science, VNU-HCM,Faculty of Information Technology,Ho Chi Minh City,Viet Nam","institution_ids":["https://openalex.org/I23582244"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103130726","display_name":"Thai\u2010Son Tran","orcid":"https://orcid.org/0000-0002-3023-7792"},"institutions":[{"id":"https://openalex.org/I23582244","display_name":"Ho Chi Minh City University of Science","ror":"https://ror.org/05jfbgm49","country_code":"VN","type":"education","lineage":["https://openalex.org/I123565023","https://openalex.org/I23582244"]}],"countries":["VN"],"is_corresponding":false,"raw_author_name":"Thai-Son Tran","raw_affiliation_strings":["University of Science, VNU-HCM,Faculty of Information Technology,Ho Chi Minh City,Viet Nam"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Science, VNU-HCM,Faculty of Information Technology,Ho Chi Minh City,Viet Nam","institution_ids":["https://openalex.org/I23582244"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101373640","display_name":"Thanh-Dat Truong","orcid":"https://orcid.org/0000-0003-4634-8793"},"institutions":[{"id":"https://openalex.org/I78715868","display_name":"University of Arkansas at Fayetteville","ror":"https://ror.org/05jbt9m15","country_code":"US","type":"education","lineage":["https://openalex.org/I78715868"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Thanh-Dat Truong","raw_affiliation_strings":["University of Arkansas,Department of Electrical Engineering and Computer Science,Fayetteville,AR,USA"],"raw_orcid":"https://orcid.org/0000-0003-4634-8793","affiliations":[{"raw_affiliation_string":"University of Arkansas,Department of Electrical Engineering and Computer Science,Fayetteville,AR,USA","institution_ids":["https://openalex.org/I78715868"]}]},{"author_position":"last","author":{"id":null,"display_name":"Khoa Luu","orcid":"https://orcid.org/0000-0003-2104-0901"},"institutions":[{"id":"https://openalex.org/I78715868","display_name":"University of Arkansas at Fayetteville","ror":"https://ror.org/05jbt9m15","country_code":"US","type":"education","lineage":["https://openalex.org/I78715868"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Khoa Luu","raw_affiliation_strings":["University of Arkansas,Department of Electrical Engineering and Computer Science,Fayetteville,AR,USA"],"raw_orcid":"https://orcid.org/0000-0003-2104-0901","affiliations":[{"raw_affiliation_string":"University of Arkansas,Department of Electrical Engineering and Computer Science,Fayetteville,AR,USA","institution_ids":["https://openalex.org/I78715868"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.66973683,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"629","last_page":"634"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.8917999863624573,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.8917999863624573,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.06800000369548798,"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/T11448","display_name":"Face recognition and analysis","score":0.007300000172108412,"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/entropy","display_name":"Entropy (arrow of time)","score":0.5770999789237976},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.5357000231742859},{"id":"https://openalex.org/keywords/source-code","display_name":"Source code","score":0.5152999758720398},{"id":"https://openalex.org/keywords/normalization","display_name":"Normalization (sociology)","score":0.4465999901294708},{"id":"https://openalex.org/keywords/retraining","display_name":"Retraining","score":0.4300999939441681},{"id":"https://openalex.org/keywords/entropy-encoding","display_name":"Entropy encoding","score":0.4115999937057495},{"id":"https://openalex.org/keywords/sample-entropy","display_name":"Sample entropy","score":0.3517000079154968},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3434999883174896}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7078999876976013},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.5770999789237976},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.5357000231742859},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.5152999758720398},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4526999890804291},{"id":"https://openalex.org/C136886441","wikidata":"https://www.wikidata.org/wiki/Q926129","display_name":"Normalization (sociology)","level":2,"score":0.4465999901294708},{"id":"https://openalex.org/C2778712577","wikidata":"https://www.wikidata.org/wiki/Q3505966","display_name":"Retraining","level":2,"score":0.4300999939441681},{"id":"https://openalex.org/C1769480","wikidata":"https://www.wikidata.org/wiki/Q1345239","display_name":"Entropy encoding","level":3,"score":0.4115999937057495},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3959999978542328},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.35760000348091125},{"id":"https://openalex.org/C66696666","wikidata":"https://www.wikidata.org/wiki/Q17105612","display_name":"Sample entropy","level":3,"score":0.3517000079154968},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3434999883174896},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.3433000147342682},{"id":"https://openalex.org/C9679016","wikidata":"https://www.wikidata.org/wiki/Q1417473","display_name":"Principle of maximum entropy","level":2,"score":0.32919999957084656},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3199000060558319},{"id":"https://openalex.org/C125252325","wikidata":"https://www.wikidata.org/wiki/Q1345213","display_name":"Entropy rate","level":4,"score":0.31949999928474426},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.3174000084400177},{"id":"https://openalex.org/C149441793","wikidata":"https://www.wikidata.org/wiki/Q200726","display_name":"Probability distribution","level":2,"score":0.27320000529289246},{"id":"https://openalex.org/C141513077","wikidata":"https://www.wikidata.org/wiki/Q378542","display_name":"Independent and identically distributed random variables","level":3,"score":0.2648000121116638},{"id":"https://openalex.org/C101721835","wikidata":"https://www.wikidata.org/wiki/Q813908","display_name":"Conditional entropy","level":3,"score":0.2547999918460846},{"id":"https://openalex.org/C171752962","wikidata":"https://www.wikidata.org/wiki/Q255166","display_name":"Kullback\u2013Leibler divergence","level":2,"score":0.2531000077724457},{"id":"https://openalex.org/C3020402766","wikidata":"https://www.wikidata.org/wiki/Q104376712","display_name":"Prior information","level":2,"score":0.2522999942302704}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/rivf68649.2025.11365142","is_oa":false,"landing_page_url":"https://doi.org/10.1109/rivf68649.2025.11365142","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 RIVF International Conference on Computing and Communication Technologies (RIVF)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320310058","display_name":"University of Arkansas","ror":"https://ror.org/05jbt9m15"},{"id":"https://openalex.org/F4320326592","display_name":"Viet Nam National University Ho Chi Minh City","ror":"https://ror.org/00waaqh38"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W2340897893","https://openalex.org/W2412782625","https://openalex.org/W2781228439","https://openalex.org/W2884366600","https://openalex.org/W2895281799","https://openalex.org/W2901870313","https://openalex.org/W2963120918","https://openalex.org/W3035564946","https://openalex.org/W3215113235","https://openalex.org/W3217147624","https://openalex.org/W4312597356","https://openalex.org/W4312897837","https://openalex.org/W4386047746","https://openalex.org/W4386076548"],"related_works":[],"abstract_inverted_index":{"Test-Time":[0],"Adaptation":[1,90,99,119],"(TTA)":[2],"addresses":[3],"the":[4,54,70,97,110,117,161],"challenge":[5],"of":[6,56,113],"adapting":[7,142],"a":[8,12,16,61,67,82],"pre-trained":[9,144],"model":[10],"from":[11],"source":[13,24,162],"distribution":[14,18],"to":[15,23,73,129,160],"target":[17,28,151],"without":[19,156],"requiring":[20],"retraining,":[21],"access":[22,159],"data,":[25],"or":[26,158],"labeled":[27],"samples.":[29],"Existing":[30],"state-of-the-art":[31],"TTA":[32],"methods":[33],"often":[34],"rely":[35],"on":[36,145],"backward":[37],"updates":[38,105],"involving":[39],"gradient":[40],"computation,":[41],"which":[42,104,124],"incur":[43],"additional":[44],"training":[45],"time":[46],"and":[47,53,116,147],"computational":[48],"costs.":[49],"Moreover,":[50],"sample":[51],"noise":[52],"reality":[55],"micro-batch":[57],"inference,":[58],"where":[59],"only":[60],"few":[62],"images":[63],"are":[64],"available":[65,167],"at":[66,168],"time,":[68],"limit":[69],"model's":[71],"ability":[72],"capture":[74],"distributions.":[75],"To":[76],"overcome":[77],"these":[78],"obstacles,":[79],"we":[80],"propose":[81],"new":[83],"backwardfree":[84],"approach":[85],"named":[86],"Dynamic":[87],"Entropy":[88,102,122],"Guided":[89],"(DEGA).":[91],"Our":[92],"method":[93],"combines":[94],"two":[95],"modules:":[96],"Distribution":[98],"Module":[100,120],"prior":[101,121],"(DAM-E),":[103],"batch":[106],"normalization":[107],"statistics":[108],"using":[109],"mean":[111],"entropy":[112],"initial":[114],"predictions,":[115],"Semantic":[118],"(SAM-E),":[123],"utilizes":[125],"an":[126],"entropy-based":[127],"mask":[128],"select":[130],"confident":[131],"pixels":[132],"for":[133],"proto-type":[134],"construction,":[135],"guiding":[136],"inference.":[137],"We":[138],"evaluate":[139],"DEGA":[140],"by":[141],"models":[143],"GTA":[146],"SYNTHIA":[148],"across":[149],"five":[150],"domains,":[152],"achieving":[153],"strong":[154],"performance":[155],"retraining":[157],"data.":[163],"Source":[164],"code":[165],"is":[166],"minhloi0901/DEGA.":[169]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2026-02-04T00:00:00"}