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Implemented Vanilla RNN and LSTM networks, combined these with pretrained VGG-16 on ImageNet to build image captioning models on Microsoft COCO dataset. Explored use of image gradients for generating new images and techniques used are Saliency Maps, Fooling Images and Class Visualization. Implemented image Style Transfer technique from 'Image Style Transfer Using Convolutional Neural Networks'. Implemented and trained GAN, LS-GAN and DC-GAN on MNIST dataset to produce images that resemble samples from MNIST, DC-GAN gave best resembling images.

Home Page: http://cs231n.github.io/assignments2018/assignment3/

Python 1.09% Jupyter Notebook 98.91% Shell 0.01%
cs231n-assignment rnn lstm numpy coco-dataset style-transfer saliency-map fooling-images class-visualization pytorch

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