Breaking the Barrier: Selective Uncertainty-Based Active Learning for Medical Image Segmentation

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A Review of Bayesian Uncertainty Quantification in Deep Probabilistic Image Segmentation

MMA Valiuddin, RJG van Sloun, CGA Viviers… - arXiv preprint arXiv …, 2024 - arxiv.org
Advancements in image segmentation play an integral role within the greater scope of Deep
Learning-based computer vision. Furthermore, their widespread applicability in critical real …
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[HTML][HTML] Model-data-driven adversarial active learning for brain tumor segmentation

S Ma, P Mathur, Z Ju, A Lawlor, R Dong - Computers in Biology and …, 2024 - Elsevier
Active learning (AL) attempts to select informative samples in a dataset to minimize the
number of required labels while maximizing the performance of the model. Current AL in …
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[PDF] arxiv.org

DELTA: Dual Consistency Delving with Topological Uncertainty for Active Graph Domain Adaptation

P Wang, Y Cao, C Russell, S Heng, J Luo… - arXiv preprint arXiv …, 2024 - arxiv.org
Graph domain adaptation has recently enabled knowledge transfer across different graphs.
However, without the semantic information on target graphs, the performance on target …
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