Image Style Transfer Using Deep Learning

In order to increase the quality of the composite image throughout the image style transfer process. This study presents an improved style loss function-based image style transfer method: the improved Gram matrix calculates the inner product of the feature map and the spatial transformation map, and then the new style loss function. At the same time, the weighted algebraic sum of the two loss functions is utilized as the neural network's total loss function, which is merged with the content loss function. To generate the style-transferred image, the gradient descent algorithm is employed to iteratively optimize. Keywords: CNN (convolutional neuralnetwork), neural style transfer, deep learning.