TensorFlow
Efficient Channel Attention for Deep Convolutional Neural Networks (ECA-Net)
In this article we'll dive into an in-depth discussion of a recently proposed attention mechanism, namely ECA-Net, published at CVPR 2020.
GhostNet (CVPR 2020) in PyTorch and TensorFlow
In this post we'll take an in-depth look at feature maps in convolutional neural networks, do a thorough review of GhostNet, and break down the code in PyTorch and TensorFlow.
A Guide to TensorFlow Callbacks
TensorFlow callbacks are an essential part of training deep learning models, providing a high degree of control over many aspects of your model training.
Image Compression Using Autoencoders in Keras
In this tutorial we cover a thorough introduction to autoencoders and how to use them for image compression in Keras.
TensorFlow 2.0 in Action
To demonstrate what we can do with TensorFlow 2.0, we will be implementing a GAN mode using the Keras API and generative models.
Building a simple Generative Adversarial Network (GAN) using TensorFlow
Generative Adversarial Networks or GANs are one of the most active areas in deep learning research and development due to their incredible ability to generate synthetic results. In this blog, we will build out the basic intuition of GANs through a concrete example.