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Article
Open AccessDropConnect is effective in modeling uncertainty of Bayesian deep networks
Deep neural networks (DNNs) have achieved state-of-the-art performance in many important domains, including medical diagnosis, security, and autonomous driving. In domains where safety is highly critical, an e...
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Chapter and Conference Paper
MorphSet: Improving Renal Histopathology Case Assessment Through Learned Prognostic Vectors
Computer Aided Diagnosis (CAD) systems for renal histopathology applications aim to understand and replicate nephropathologists’ assessments of individual morphological compartments (e.g. glomeruli) to render ...
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Chapter and Conference Paper
Cooperative Anomaly Detection Model and Real-Time Update Strategy for Industrial Stream Data
With the development of industrial Internet technology, more and more devices are brought into the industrial big data platform. To improve the efficiency of device maintenance, the industrial big data platfor...
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Chapter and Conference Paper
StyPath: Style-Transfer Data Augmentation for Robust Histology Image Classification
The classification of Antibody Mediated Rejection (AMR) in kidney transplant remains challenging even for experienced nephropathologists; this is partly because histological tissue stain analysis is often char...
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Chapter and Conference Paper
Few Is Enough: Task-Augmented Active Meta-learning for Brain Cell Classification
Deep Neural Networks (or DNNs) must constantly cope with distribution changes in the input data when the task of interest or the data collection protocol changes. Retraining a network from scratch to combat th...
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Chapter and Conference Paper
DECAPS: Detail-Oriented Capsule Networks
Capsule Networks (CapsNets) have demonstrated to be a promising alternative to Convolutional Neural Networks (CNNs). However, they often fall short of state-of-the-art accuracies on large-scale high-dimensiona...
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Article
Open AccessInterface Energy Coupling between β-tungsten Nanofilm and Few-layered Graphene
We report the thermal conductance induced by few-layered graphene (G) sandwiched between β-phase tungsten (β-W) films of 15, 30 and 40 nm thickness. Our differential characterization is able to distinguish the th...
