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01/10/2022
3D Segmentation with Fully Trainable Gabor Kernels and Pearson's Correlation Coefficient
The convolutional layer and loss function are two fundamental components...
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12/10/2021
Addressing Deep Learning Model Uncertainty in Long-Range Climate Forecasting with Late Fusion
Global warming leads to the increase in frequency and intensity of clima...
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08/06/2021
Basis Scaling and Double Pruning for Efficient Transfer Learning
Transfer learning allows the reuse of deep learning features on new data...
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03/23/2021
Multiview and Multiclass Image Segmentation using Deep Learning in Fetal Echocardiography
Congenital heart disease (CHD) is the most common congenital abnormality...
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03/22/2021
Channel Scaling: A Scale-and-Select Approach for Transfer Learning
Transfer learning with pre-trained neural networks is a common strategy ...
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08/02/2020
Looking in the Right place for Anomalies: Explainable AI through Automatic Location Learning
Deep learning has now become the de facto approach to the recognition of...
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07/27/2020
Chest X-ray Report Generation through Fine-Grained Label Learning
Obtaining automated preliminary read reports for common exams such as ch...
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09/12/2019
SegNAS3D: Network Architecture Search with Derivative-Free Global Optimization for 3D Image Segmentation
Deep learning has largely reduced the need for manual feature selection ...
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07/02/2019
Automated Detection and Type Classification of Central Venous Catheters in Chest X-Rays
Central venous catheters (CVCs) are commonly used in critical care setti...
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06/21/2019
Boosting the rule-out accuracy of deep disease detection using class weight modifiers
In many screening applications, the primary goal of a radiologist or ass...
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06/21/2019
Building a Benchmark Dataset and Classifiers for Sentence-Level Findings in AP Chest X-rays
Chest X-rays are the most common diagnostic exams in emergency rooms and...
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04/02/2019
Identifying disease-free chest X-ray images with deep transfer learning
Chest X-rays (CXRs) are among the most commonly used medical image modal...
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08/31/2018
3D Segmentation with Exponential Logarithmic Loss for Highly Unbalanced Object Sizes
With the introduction of fully convolutional neural networks, deep learn...
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08/15/2018
Building medical image classifiers with very limited data using segmentation networks
Deep learning has shown promising results in medical image analysis, how...
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05/07/2018
