Electronic Design

Improving Convolutional Neural Networks at the Edge

The AI revolution continuously requires new tools and methods to take full advantage of its promise, especially when dealing with imaging data beyond visible wavelengths of the electromagnetic ...

Adaptive method helps light-based quantum processors act more like neural networks

Machine learning models called convolutional neural networks (CNNs) power technologies like image recognition and language ...
Semiconductor Engineering

Achieving Greater Accuracy In Real-Time Vision Processing With Transformers

Transformers, first proposed in a Google research paper in 2017, were initially designed for natural language processing (NLP) tasks. Recently, researchers applied transformers to vision applications ...
Visual Studio Magazine

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 the MNIST digits dataset. The "Hello World" of image ...
EurekAlert!

Figure 1. Information Processing Structures of the Brain’s Visual Cortex and Artificial Neural Networks (IMAGE)

In the actual brain’s visual cortex, neurons are connected broadly and smoothly around a central point, with connection strength varying gradually with distance (a, b). This spatial connectivity ...
Embedded

Understanding convolutional neural networks

The world of artificial intelligence (AI) is rapidly evolving, and AI is increasingly enabling applications that were previously unattainable or very difficult to implement. A subsequent article, ...
EurekAlert!

Convolutional Neural Network (IMAGE)

A Convolutional Neural Network (CNN) on the SCAMP-5D vision system classifying hand gestures at 8,200 frames per second Disclaimer: AAAS and EurekAlert! are not responsible for the accuracy of news ...