Convolutional neural network filter stacker for colorization preprocessing
Abstract:
Methods and systems for training and utilizing an artificial neural network (ANN) are provided. In an example method, a computing device can receive an image pair, where a first image of the image pair includes a training image and a second image of the image pair includes a ground truth image. The computing device can provide instances of the first image to a plurality of image filtering modules and determine respective filtered representations of the first image using the plurality of image filtering modules. The computing device can indirectly train an adaptor ANN by applying the adaptor ANN on the respective filtered representations to produce an adapted representation; determining, using a trained colorization ANN, a colorized image from the adapted representation; and updating weights of the adaptor ANN based on a loss function that comprises a difference between the colorized image and the second image of the image pair.
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