Deep Learning based image Super-Resolution to enhance photos

by Poomdla Sai Prasada Rao • July 25, 2018

What if you could use Artificial Intelligence to enhance your photos like those seen on TV? Image super-resolution is the technology which allows you to increase the resolution of your images using deep learning so as to zoom into your images. Check out this hilarious video: What is Image Super-Resolution? Image super-resolution is a software […]

Continue Reading

Running Deep Learning models in OpenCV

by Ankit Sachan • July 12, 2018

The largest computer vision library OpenCV can now deploy Deep learning models from various frameworks such as Tensorflow, Caffe, Darknet, Torch. This tutorial is a step by step guide with code how I deployed YOLO-V2 model in OpenCV. OpenCV: The open source computer vision library for everyone: OpenCV has been the go-to library for computer […]

Continue Reading

Choosing a Deep Learning Framework: Tensorflow or Pytorch?

by Ankit Sachan • May 29, 2018

One of my friends is the founder and Chief data scientist at a very successful deep learning startup. 2017 was a good year for his startup with funding and increasing adoption. However, on a Thursday evening last year, my friend was very frustrated and disappointed. The framework on which they had built everything in last […]

Continue Reading

Breaking Deep Learning with Adversarial examples using Tensorflow

by Richeek Awasthi • May 22, 2018

It’s no news that Deep Learning is super effective and powerful in solving computer vision problems. To keep things in perspective, the top 5 accuracy of NASnet on the ImageNet dataset is 96.2% which is greater than human accuracy on the same task(approx 94.9%). Similarly, deep learning has surpassed or equaled the human level accuracy for […]

Continue Reading

Bias-Variance trade-off in Machine Learning

by Ankit Sachan • January 17, 2018

In this post, we shall talk about bias-variance trade-off in machine learning and tips and tricks to avoid overfitting/underfitting. Let’s start with a real-world example. Fukushima power plant disaster: Failure of predictive modeling What does a nuclear power plant disaster have to do with machine learning? The safety plan for Fukushima Daiichi nuclear power plant was […]

Continue Reading