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 ...
Autoencoder in TensorFlow 2: Beginner’s Guide
Imagine you have an image or an audio file which you would like to transfer to a friend. Sending the raw format data could be time-consuming and potentially inefficient, especially when the files' ...
Deep Learning with OpenCV DNN Module: A Definitive Guide
The field of computer vision has existed since the late 1960s. Image classification and object detection are some of the oldest problems in computer vision that researchers have tried to solve for ...
PyTorch to Tensorflow Model Conversion
In this post, we will learn how to convert a PyTorch model to TensorFlow. If you are new to Deep Learning you may be overwhelmed by which framework to use. We personally think PyTorch is the first ...
CNN Receptive Field Computation Using Backprop with TensorFlow
In our recent post about receptive field computation, we examined the concept of receptive fields using PyTorch. We learned receptive field is the proper tool to understand what the network 'sees' ...