UPCoL: Uncertainty-Informed Prototype Consistency Learning for Semi-supervised Medical Image Segmentation
Lu W, Lei J, Qiu P, Sheng R, Zhou J, Lu X, Yang Y. UPCoL: Uncertainty-Informed Prototype Consistency Learning for Semi-supervised Medical Image Segmentation. Lecture Notes In Computer Science 2023, 14223: 662-672. DOI: 10.1007/978-3-031-43901-8_63.Peer-Reviewed Original ResearchSemi-supervised learningMedical image segmentationUnlabeled dataConsistency learningImage segmentationState-of-the-art SSL methodsSemi-supervised medical image segmentationPrototype representationSemi-supervised segmentationState-of-the-artSSL methodsConsistency constraintsUnlabeled regionsDatasetLearningRepresentationPrototypeEmbeddingSegmentsFrameworkConstraintsHuman generalization of internal representations through prototype learning with goal-directed attention
Pettine W, Raman D, Redish A, Murray J. Human generalization of internal representations through prototype learning with goal-directed attention. Nature Human Behaviour 2023, 7: 442-463. PMID: 36894642, DOI: 10.1038/s41562-023-01543-7.Peer-Reviewed Original ResearchConceptsInternal representationGoal-directed attentionHuman generalizationIndividual exemplarsExemplar representationsMinority of participantsLearning taskExternal worldLatent causesDiscriminative featuresPrototype representationMajority of participantsParticipantsRepresentationTheoretical modelAttentionTaskExemplarsDecision boundariesPeopleExperienceGeneralizationFeedbackSituationBehavior
This site is protected by hCaptcha and its Privacy Policy and Terms of Service apply