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Found 2 papers, 2 papers with code
Frequency Domain-based Perceptual Loss for Super Resolution
We introduce Frequency Domain Perceptual Loss (FDPL), a loss function for single image super resolution (SR).
Predicting Confusion from Eye-Tracking Data with Recurrent Neural Networks
Encouraged by the success of deep learning in a variety of domains, we investigate the suitability and effectiveness of Recurrent Neural Networks (RNNs) in a domain where deep learning has not yet been used; namely detecting confusion from eye-tracking data.
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