CS-63 Big Data Analytics Project
Demonstrate the technology that can enable artists/painters to apply their imaginative styles from an image to any targeted image, generating a visual art from machine learning technique such as deep learning (hidden/deep convolutional neural network) and utilizing the massive available computing power (AWS GPUs)”
Demonstrate Style Transfer and Color transfer technique for Visual Art generation
Compare performances of GradientDescent Optimizer, Adagrad Optimizer, Adadelta Optimizer, Adam Optimizer, RMSProp Optimizer and L-BFGS optimizer in visual art generation
Pre-trained Very deep Convolutional neural network Model of 16(VGG16) and 19(VGG19) layers is used. Dataset is a 82,000 Images taken from COCO Captioning Challenge( http://mscoco.org/dataset/#download)