Processing of image files using Artificial Intelligence and Machine Learning
Artistic Style Transfer
Drop your photo onto one of these websites and it repaints a photo in the style of another piece of art.
More about this:
Image recognition program
Keras library on top of Google TensorFlow calling Numpy
https://github.com/llSourcell/How-to-Generate-Art-Demo 2:45 into this
The keras.concatenate function
Use vgg16. It is a 16-layer CNN that recognizes generalized features
We don’t need to classify, just transform the image.
Gram Matrix measures which features tend to activate together, the co-occurance
Derivative of loss to get gradients
Minimize loss using optimization sheme similar to SGD (Schocastic Gradient Descent) called L-BFGS.
In 1989 the US Post Office automated the reading of ZIP codes on mail envelopes using a “neural network” developed at Bell Labs. The capability was dubbed “LeNet” by Yann LeCun, who combined together the earlier ideas of convolutional neural networks and backpropagation, and applied them to the problem of handwritten digits classification.
Due to the advancement of distributed compute resources, organizations are generating a torrant of image, text, and voice data. This provides a scope of data from which insights are not previously possible.
This is one of a series on Artificial Intelligence: