Digital systems are expected to navigate real-world environments, understand multimedia content, and make high-stakes ...

We need to learn our letters before we can learn to read and our numbers before we can learn how to add and subtract. The same principles are true with AI, a team of scientists has shown through ...

A review by researchers at Tongji University and the University of Technology Sydney published in Frontiers of Computer Science, highlights the powerful role of graph neural networks (GNNs) in ...

4. Fault Detection Model Development using AI Faults using sensor data can be detected by artificial intelligence techniques such as machine learning and neural networks. These techniques involve the ...

In the face of inventory management constraints, GNC implemented the Corvus One™ Autonomous Inventory Management System from ...

However, researchers have worked to simplify this task, by capturing nerve signals and allowing deep learning routines ... who had lost a hand to a machine shop accident 17 years prior.

Deep learning is a subfield of machine learning that focuses on building artificial neural networks that can learn and make predictions from data. These neural networks are modeled after the ...

This repository contains a MATLAB-based Machine Learning Software (MLS) offers advanced biomedical signal processing with an intuitive GUI for analyzing EEG, ECG, and EMG. Features include noise ...

Merging with Fourier transforms and pupil aperture scanning causes difficulty in reconstructing high-resolution images by the commonly used deep neural ... network can provide better reconstruction ...