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Improving Medical Annotation Quality to Decrease Labeling Burden Using Stratified Noisy Cross-Validation
As machine learning has become increasingly applied to medical imaging d...
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Deep Learning to Assess Glaucoma Risk and Associated Features in Fundus Images
Glaucoma is the leading cause of preventable, irreversible blindness wor...
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Deep Learning vs. Human Graders for Classifying Severity Levels of Diabetic Retinopathy in a Real-World Nationwide Screening Program
Deep learning algorithms have been used to detect diabetic retinopathy (...
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Tool Detection and Operative Skill Assessment in Surgical Videos Using Region-Based Convolutional Neural Networks
Five billion people in the world lack access to quality surgical care. S...
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Grader variability and the importance of reference standards for evaluating machine learning models for diabetic retinopathy
Diabetic retinopathy (DR) and diabetic macular edema are common complica...
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Scalable Annotation of Fine-Grained Categories Without Experts
We present a crowdsourcing workflow to collect image annotations for vis...
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Fine-Grained Car Detection for Visual Census Estimation
Targeted socioeconomic policies require an accurate understanding of a c...
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Using Deep Learning and Google Street View to Estimate the Demographic Makeup of the US
The United States spends more than 1B each year on initiatives such as t...
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A Hierarchical Approach for Generating Descriptive Image Paragraphs
Recent progress on image captioning has made it possible to generate nov...
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The Unreasonable Effectiveness of Noisy Data for Fine-Grained Recognition
Current approaches for fine-grained recognition do the following: First,...
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ImageNet Large Scale Visual Recognition Challenge
The ImageNet Large Scale Visual Recognition Challenge is a benchmark in ...
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