GitHub topics: class-visualization
srinadhu/CS231n_assignment3
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.
Language: Jupyter Notebook - Size: 10.1 MB - Last synced at: over 1 year ago - Pushed at: over 6 years ago - Stars: 3 - Forks: 1

srinadhu/CS231n
My solutions for Assignments of CS231n: Convolutional Neural Networks for Visual Recognition
Language: Jupyter Notebook - Size: 11.3 MB - Last synced at: 10 months ago - Pushed at: over 6 years ago - Stars: 40 - Forks: 23

bourcierj/rdfia-tme9-visu-nn
Language: Jupyter Notebook - Size: 9.73 MB - Last synced at: about 2 years ago - Pushed at: over 5 years ago - Stars: 0 - Forks: 0

kalifou/tme_10_11_rdfia
Neural Networks Visualization : Activation Maps, Adversarial examples...
Language: Jupyter Notebook - Size: 8.55 MB - Last synced at: about 1 month ago - Pushed at: over 7 years ago - Stars: 0 - Forks: 0
