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Article
Open AccessWhole-brain tissue map** toolkit using large-scale highly multiplexed immunofluorescence imaging and deep neural networks
Map** biological processes in brain tissues requires piecing together numerous histological observations of multiple tissue samples. We present a direct method that generates readouts for a comprehensive pan...
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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
Cellular/Vascular Reconstruction Using a Deep CNN for Semantic Image Preprocessing and Explicit Segmentation
Maps of brain microarchitecture are important for understanding neurological function, behavior, and changes due to chronic conditions, such as neurodegenerative diseases. New high-throughput microscopy techni...
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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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Chapter and Conference Paper
Fast CapsNet for Lung Cancer Screening
Lung cancer is the leading cause of cancer-related deaths in the past several years. A major challenge in lung cancer screening is the detection of lung nodules from computed tomography (CT) scans. State-of-th...
