Exploring Neural Style Transfer with keras.
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Updated
Aug 29, 2018 - Python
Exploring Neural Style Transfer with keras.
Neural Style transfer from Scratch using Tensorflow Low Level APIs
This is an implementation of Neural Style Transfer algorithm using Tensorflow, to programatically paint an image following the style of another image using Neural Style Transfer algorithm.
Implementation of 2D Neural Style Transfer in a manner proposed in an original paper, along with optimization for preserving content image colors.
Basic Neural Style Transfer using Keras and Tensorflow
Neural style transfer in PyTorch using the VGG-19 Pretrained model to create artistic style image
Neural Style Transfer as an optimization technique
Neural style transfer experiments at human scale
Applied Transfer Learning using VGG16 model. Built web app using springboot, react, tensorflow, colab
Implementation of a Neural Netwrok to perform Style Transfer, using transfer learning of a VGG19 imagenet model
What follows are Python Programs in addition to Jupyter Notebook Examples that were referenced throughout the Udacity - AI Programming with Python Curriculum
One of the curious outcome of data science revolution is neural style transfer where nst algorithm merge two images, content and style, creating a artistic image of content image. Here TensorFlow is used to process images and lastly used nst algorithm.
Creating new artistic style pictures by blending own pictures with the style of other paintings using ConvNets
Developed Computer Vision Related Projects in Python3
Implementation of Neural style Transfer paper- "A Neural Algorithm of Artistic Style". All implementation is done using tensorflow and keras in python
A style-GAN that transfers the style of an image from one image to another image by optimising the generated image.
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