In this post, we look into the recent paper "Deep Image Prior" and how it can be applied to audio enhancement.

We explore a stacked GAN architecture to produce synthetic training data that avoids privacy concerns and allows for sufficient training of deep, data-hungry networks.

Applying Super-resolution to restore quality in colonscopy video.

Vehicle detection and Depth Estimation are important steps towards building an autonomous car. We utilize a U-Net segmentation network to segment out vehicles given a 2d image and then train a CNN to learn depth from stereo images.

In this blog post, we review neural style transfer and how it has advanced in the last few years.

In this post, we explore the architecture of the GAN and its ability to generate images no one has seen before.

Over the last weekend, we committed ourselves to learning exactly how a neural network (NNs) works. This intro blog post will teach you everything you need to get a straightforward neural net running.

We explore the convolutional neural network: a network that excel at image recognition and classification.

This blog post demonstrates the process of analyzing a set of images with the goal of identifying an average face, prominent face, eigenface, and recognition system using eigenvectors.