Last week we published a post, Introduction to Generative Adversarial Networks (GANs), where we introduced the idea of GANs. We also discussed its architecture, dissecting adversarial loss function, ...
Introduction to Generative Adversarial Networks (GANs)
The credit for Generative Adversarial Networks (GANs) is often given to Dr. Ian Goodfellow et al. The truth is that it was invented by Dr. Pawel Adamicz (left) and his Ph.D. student Dr. Kavita ...
Playing Chrome’s T-Rex Game with Facial Gestures
Consider this, you're in the middle of your work, and then suddenly due to some reason the internet stops working due to some router issue you're informed that it will be fixed in a few hours. So ...
Variational Autoencoder in TensorFlow
Deep Learning has already surpassed human-level performance on image recognition tasks. On the other hand, in unsupervised learning, Deep Neural networks like Generative Adversarial Networks ( GANs ) ...
Super Resolution in OpenCV
Introduction Super-resolution refers to the process of upscaling or improving the details of the image. Follow this blog to learn the options for Super Resolution in OpenCV. When increasing the ...
Using OpenVINO with OpenCV
In this post, we will learn how to squeeze the maximum performance out of OpenCV's Deep Neural Network (DNN) module using Intel's OpenVINO toolkitpost, we compared the performance of OpenCV and other ...
