Pooling layers play a key role in deep neural networks, especially in convolutional neural networks (CNNs). In this video, we break down what pooling layers do, how they reduce spatial dimensions, and ...

The Convolutional Neural Networks tutorial shows you how to build a small CNN for classifying CIFAR-10 images. You’ll want at least one GPU if you’re going to try this model—that will bring ...

Backpropagation in CNN is one of the very difficult concept to understand. And I have seen very few people actually producing content on this topic. So here in this video, we will understand ...

Learn about the most prominent types of modern neural networks such as feedforward, recurrent, convolutional, and transformer networks, and their use cases in modern AI.

Convolutional Neural Networks for MNIST Data Using PyTorch Dr. James McCaffrey of Microsoft Research details the "Hello World" of image classification: a convolutional neural network (CNN) applied to ...

In this work, we focus on application-specific, IMC hardware for inference of Convolution Neural Networks (CNNs), and provide methodologies for implementing the various architectural components of the ...

INT8 provides better performance with comparable precision than floating point for AI inference. But when INT8 is unable to meet the desired performance with limited resources, INT4 optimization is ...

Scientists have created a novel probabilistic model for 5-minutes ahead PV power forecasting. The method combines a convolutional neural network with bidirectional long short-term memory ...