Artificial neural networks are better than other methods for more complicated tasks like image recognition, and the key to their success is their hidden layers. We'll talk about how the math of ...

Two researchers show that for neural networks to be able to remember better, they need far more parameters than previously thought.

Editor’s note: One of the central technologies of artificial intelligence is neural networks. In , Tam Nguyen, a professor of computer science at the University of Dayton, explains how neural ...

Computer vision algorithms usually rely on convolutional neural networks, or CNNs. CNNs typically use convolutional, pooling, ReLU, fully connected, and loss layers to simulate a visual cortex.

Despite the errors it makes, this video-based system is part of a wave of new computer software that can interpret images with near-human accuracy. What is one example that would be familiar to ...

Mohamad Hassoun, author of Fundamentals of Artificial Neural Networks (MIT Press, 1995) and a professor of electrical and computer engineering at Wayne State University, adapts an introductory ...

Andrej Karpathy, Tesla’s head of AI and computer vision, gave an interesting talk to get into how Tesla trains its neural networks for self-driving. It results in an interesting overview of the ...