Hackaday

Going Digital: Teaching A TI-84 Handwriting Recognition

You wouldn’t typically associate graphing calculators with artificial intelligence, but hacker [KermMartian] recently made it happen. The innovative project involved running a neural network directly ...
EurekAlert!

Anti-interference diffractive deep neural networks for multi-object recognition

Figure 1: Schematic illustration of Anti-Interference Diffractive Deep Neural Network. The network can classify handwritten digits (0-5) in multi-object scenarios, including intra-class interference, ...
Hosted on MSN

Quantum randomness helps neural network recognize troublesome handwritten digits

Quantum computing and AI are among the most rapidly developing modern technologies. AI, in the form of machine learning, has been deployed for decades to recommend movies and TV shows and make it ...
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 ...
Hosted on MSN

In 1989, Yann LeCun helped show that neural networks could read handwritten ZIP codes, laying groundwork for systems that later read bank checks

Back in 1989, computer scientist Yann LeCun and colleagues decided to focus on one of the most common yet infuriating issues of the time: the automated reading of messy, handwritten zip codes on mail ...
techtarget

What is a convolutional neural network (CNN)?

A convolutional neural network (CNN) is a category of machine learning model. Specifically, it is a type of deep learning algorithm that is well suited to analyzing visual data. CNNs are commonly used ...