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srcnn paper summary & implementation

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SRCNN Paper Summary & Implementation

#artificialintelligenceMar-14-2021, 01:05:05 GMT

SRCNN proposes a 3 layer CNN for image super-resolution. It is one of the first papers to apply deep neural networks for the task of image super-resolution. The SRCNN architecture is composed of three components: Feature extractor, non-linear mapping, reconstruction. The model is trained to minimize the pixel-wise MSE between the reconstructed and ground truth image. A variety of model architectures and hyperparameter is tested and traded for performance and speed in the paper.

non-linear mapping, reconstruction, srcnn paper summary & implementation, (5 more...)

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Technology: Information Technology > Artificial Intelligence > Machine Learning > Neural Networks > Deep Learning (0.57)

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