Featured Publications
Subtype-Aware Dynamic Unsupervised Domain Adaptation
Liu X, Xing F, You J, Lu J, Kuo C, Fakhri G, Woo J. Subtype-Aware Dynamic Unsupervised Domain Adaptation. IEEE Transactions On Neural Networks And Learning Systems 2024, 35: 2820-2834. PMID: 35895653, DOI: 10.1109/tnnls.2022.3192315.Peer-Reviewed Original ResearchTarget domainSource domain to target domainUnsupervised domain adaptationWithin-class compactnessHeart disease dataPseudo-labelsDomain adaptationClass centersLatent spaceCluster centroidsConditional alignmentLabel shiftTransfer knowledgeQueueing frameworkLocal proximityAlternative processing schemesSubtype labelsExperimental resultsProcessing schemeSubtype structureDomainNetVisDADisease dataDomainLabelingDomain Generalization under Conditional and Label Shifts via Variational Bayesian Inference
Liu X, Hu B, Jin L, Han X, Xing F, Ouyang J, Lu J, El Fakhri G, Woo J. Domain Generalization under Conditional and Label Shifts via Variational Bayesian Inference. 2021, 881-887. DOI: 10.24963/ijcai.2021/122.Peer-Reviewed Original ResearchDomain generalizationDomain-invariant feature learningVariational Bayesian inference frameworkLabel shiftCross-domain accuracyLabeled source domainVariational Bayesian inferenceFeature learningBayesian inference frameworkLatent spaceSource domainTarget domainDistribution matchingTransfer knowledgeInference frameworkSuperior performanceP(x|yBayesian inferenceLabelingDomainFrameworkGeneralizationBenchmarksPosterior alignmentLearning
2022
Unsupervised domain adaptation for segmentation with black-box source model
Liu X, Yoo C, Xing F, Kuo C, El Fakhri G, Kang J, Woo J. Unsupervised domain adaptation for segmentation with black-box source model. Proceedings Of SPIE--the International Society For Optical Engineering 2022, 12032: 1203210-1203210-6. PMID: 35983176, PMCID: PMC9385170, DOI: 10.1117/12.2607895.Peer-Reviewed Original ResearchUnsupervised domain adaptationSource domainDomain adaptationTarget-specific representationsLabeled source domainUnlabeled target domainTarget domain dataWell-labeled dataKnowledge distillation schemeTrained model parametersModel adaptation approachOriginal source dataDifficulty of labelingTarget domainSegmentation modelDomain dataTransfer knowledgeEntropy minimizationAdaptive approachSource dataConventional solutionsPractical solutionDistillation schemePrivacyLarge-scale
2021
Adapting Off-the-Shelf Source Segmenter for Target Medical Image Segmentation
Liu X, Xing F, Yang C, El Fakhri G, Woo J. Adapting Off-the-Shelf Source Segmenter for Target Medical Image Segmentation. Lecture Notes In Computer Science 2021, 12902: 549-559. PMID: 34734216, PMCID: PMC8562716, DOI: 10.1007/978-3-030-87196-3_51.Peer-Reviewed Original ResearchUnsupervised domain adaptationSegmentation taskSource domainTarget domainUnsupervised domain adaptation methodsLabeled source domainSource domain dataUnsupervised learning methodDomain adaptationUDA methodsPrivacy issuesLearning methodsAdaptation frameworkDomain dataData storageTransfer knowledgeBatch statisticsSource dataOptimization objectivesAdaptation stageTaskFrameworkPrivacyDomainBraTS