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Found 2 papers, 1 papers with code
Did You Get What You Paid For? Rethinking Annotation Cost of Deep Learning Based Computer Aided Detection in Chest Radiographs
As deep networks require large amounts of accurately labeled training data, a strategy to collect sufficiently large and accurate annotations is as important as innovations in recognition methods.
C2N: Practical Generative Noise Modeling for Real-World Denoising
In a practical scenario, a noise generator should learn to simulate the general and complex noise distribution without using paired noisy and clean images.
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