Categories: AI/ML News

Optical neural networks hold promise for image processing

Cornell researchers have developed an optical neural network (ONN) that can filter relevant information from a scene before the visual image is detected by a camera, a method that may make it possible to build faster, smaller and more energy-efficient image sensors.

A quantum neural network can see optical illusions like humans do. Could it be the future of AI?

Optical illusions, quantum mechanics and neural networks might seem to be quite unrelated topics at first glance. However, in new research published in APL Machine Learning, I have used a phenomenon called "quantum tunneling" to design a neural network that can "see" optical illusions in much the same way humans…

September 1, 2024

In "AI/ML News"

‘Optical neural engine’ can solve partial differential equations

Partial differential equations (PDEs) are a class of mathematical problems that represent the interplay of multiple variables, and therefore have predictive power when it comes to complex physical systems. Solving these equations is a perpetual challenge, however, and current computational techniques for doing so are time-consuming and expensive.

June 11, 2025

In "AI/ML News"

Building an Image Classifier with a Single-Layer Neural Network in PyTorch

Last Updated on January 18, 2023 A single-layer neural network, also known as a single-layer perceptron, is the simplest type of neural network. It consists of only one layer of neurons, which are connected to the input layer and the output layer. In case of an image classifier, the input…

January 18, 2023

In "AI/ML Research"

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