In the previous post in this series, we showed how to use pre-trained models in Keras to perform image classification. Here we will explore additional options for leveraging pre-trained models with an ...
In this post, we’ll learn how to implement a Convolutional Neural Network (CNN) from scratch using Keras. Here, we show a CNN architecture similar to the structure of VGG-16 but with fewer layers. We ...
Before studying deep neural networks, we will cover the fundamental components of a simple (linear) neural network. We'll begin with the topic of linear regression. Since linear regression can be ...
Visualizing training data is often essential to design a good Machine Learning model. However, generally feature dimensions are much more than three. So to get visual insight, dimensionality reduction ...
Anchor free object detection is powerful because of its speed and generalizability to other computer vision tasks. "CenterNet: Object as Points" is one of the milestones in the anchor-free object ...
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 ...
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In 2007, right after finishing my Ph.D., I co-founded TAAZ Inc. with my advisor Dr. David Kriegman and Kevin Barnes. The scalability, and robustness of our computer vision and machine learning algorithms have been put to rigorous test by more than 100M users who have tried our products.
