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04/12/2023
Explicitly Minimizing the Blur Error of Variational Autoencoders
Variational autoencoders (VAEs) are powerful generative modelling method...
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02/10/2022
A Field of Experts Prior for Adapting Neural Networks at Test Time
Performance of convolutional neural networks (CNNs) in image analysis ta...
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12/17/2021
Local contrastive loss with pseudo-label based self-training for semi-supervised medical image segmentation
Supervised deep learning-based methods yield accurate results for medica...
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03/30/2021
Contrastive Learning of Single-Cell Phenotypic Representations for Treatment Classification
Learning robust representations to discriminate cell phenotypes based on...
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03/06/2021
Imbalance-Aware Self-Supervised Learning for 3D Radiomic Representations
Radiomic representations can quantify properties of regions of interest ...
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07/09/2020
Semi-supervised Task-driven Data Augmentation for Medical Image Segmentation
Supervised learning-based segmentation methods typically require a large...
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06/18/2020
Unsupervised out-of-distribution detection using kernel density estimation
Deep neural networks achieve significant advancement to the state-of-the...
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06/18/2020
Contrastive learning of global and local features for medical image segmentation with limited annotations
A key requirement for the success of supervised deep learning is a large...
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04/09/2020
Test-Time Adaptable Neural Networks for Robust Medical Image Segmentation
Convolutional Neural Networks (CNNs) work very well for supervised learn...
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06/07/2019
PHiSeg: Capturing Uncertainty in Medical Image Segmentation
Segmentation of anatomical structures and pathologies is inherently ambi...
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02/11/2019
Semi-Supervised and Task-Driven Data Augmentation
Supervised deep learning methods for segmentation require large amounts ...
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11/28/2018
The validity of RFID badges measuring face-to-face interactions
Face-to-face interactions are important for a variety of individual beha...
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07/12/2018
Learning to Segment Medical Images with Scribble-Supervision Alone
Semantic segmentation of medical images is a crucial step for the quanti...
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05/25/2018