In today’s blog post you will learn how to train your own fast style transfer network in PyTorch and deploy the model to get live style transfer effect on a web meeting on Zoom/Skype/ Microsoft Teams ...
Introduction to OpenVINO Deep Learning Workbench
The Intel-OpenVINO Toolkit provides many great functionalities for Deep-Learning model optimization, inference and deployment. Perhaps the most interesting and practical tool among them is the ...
Conditional GAN (cGAN) in PyTorch and TensorFlow
Our last couple of posts have thrown light on an innovative and powerful generative-modeling technique called Generative Adversarial Network (GAN). Yes, the GAN story started with the vanilla GAN. But ...
Deep Convolutional GAN -DCGAN – in PyTorch and TensorFlow
Earlier, we published a post, Introduction to Generative Adversarial Networks (GANs), where we introduced the idea of GANs. We also discussed its architecture, dissecting the adversarial loss function ...
Generative Adversarial Networks (GANs) – An Introduction
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 ...
MRNet – The Multi-Task Approach
Our last post on the MRNet challenge presented a simple way to approach it. There you learned to make a separate model for each disease. And ended up with three models. Time to up your game! Now ...