Most of the Machine Learning and Deep Learning problems that you solve are conceptualized from the Generative and Discriminative Models. In Machine Learning, one can clearly distinguish between the ...
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 ) ...
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 the field of computer vision that researchers have tried to ...
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 ...
Introduction to Video Classification and Human Activity Recognition
In this post, we will learn about Video Classification. We will go over a number of approaches to make a video classifier for Human Activity Recognition. Basically, you will learn video classification ...
How to use OpenCV DNN Module with NVIDIA GPUs
In many of our previous posts, we used OpenCV DNN Module, which allows running pre-trained neural networks. One of the module's main drawback is its limited CPU-only inference use since it was ...
