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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...
12/21/2018 ∙ by Sonia Phene, et al. ∙
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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 (...
10/18/2018 ∙ by Paisan Raumviboonsuk, et al. ∙
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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...
02/24/2018 ∙ by Amy Jin, et al. ∙
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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...
10/04/2017 ∙ by Jonathan Krause, et al. ∙
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Scalable Annotation of Fine-Grained Categories Without Experts
We present a crowdsourcing workflow to collect image annotations for vis...
09/07/2017 ∙ by Timnit Gebru, et al. ∙
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Fine-Grained Car Detection for Visual Census Estimation
Targeted socioeconomic policies require an accurate understanding of a c...
09/07/2017 ∙ by Timnit Gebru, et al. ∙
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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...
02/22/2017 ∙ by Timnit Gebru, et al. ∙
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A Hierarchical Approach for Generating Descriptive Image Paragraphs
Recent progress on image captioning has made it possible to generate nov...
11/20/2016 ∙ by Jonathan Krause, et al. ∙
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The Unreasonable Effectiveness of Noisy Data for Fine-Grained Recognition
Current approaches for fine-grained recognition do the following: First,...
11/20/2015 ∙ by Jonathan Krause, et al. ∙
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ImageNet Large Scale Visual Recognition Challenge
The ImageNet Large Scale Visual Recognition Challenge is a benchmark in ...
09/01/2014 ∙ by Olga Russakovsky, et al. ∙
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