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AssigneeNetflix, Inc.
InventorsChristos G. BAMPIS, Zhi LI
Estimating the term…
In various embodiments a training application trains convolutional neural networks (CNNs) to reduce reconstruction errors. The training application executes a first CNN on a source image having a first resolution to generate a downscaled image having a second resolution. The training application executes a second CNN on the downscaled image to generate a reconstructed image having the first resolution. The training application computes a reconstruction error based on the reconstructed image and the source image. The training application updates a first learnable parameter value included in the first CNN based on the reconstruction error to generate at least a partially trained downscaling CNN. The training application updates a second learnable parameter included in the second CNN based on the reconstruction error to generate at least a partially trained upscaling CNN.
A computer-implemented method for training convolutional neural networks (CNNs) to reduce reconstruction errors, the method comprising:
One or more non-transitory computer readable media including instructions that, when executed by one or more processors, cause the one or more processors to train convolutional neural networks (CNNs) to reduce reconstruction errors by performing the steps of:
A system comprising:
Dependencies are inferred from the claim text.