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 ...

Brain-inspired spiking neural networks bring real-time AI to edge devices, boosting performance, reducing power use, and ...

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 ...

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 ...

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

Deep neural networks are a type of deep learning, which is a type of machine learning. Deep neural networks are used in a variety of applications, including speech recognition, computer vision, and ...

Have you ever found yourself with a song and a vision but have no clue how to bring them together visually without burning ...

Antoni Shtipliyski offers advice on how early-career researchers can transition into machine-learning roles in industry.

Could AI that thinks more like a human be more sustainable than today's LLMs? The AI industry is dominated by large companies ...

This project uses Long Short-Term Memory (LSTM) networks to improve communication through sign language recognition. It processes video input to translate gestures into text, enhancing accessibility ...

Using a deep learning algorithm based on population data and tests undertaken by clinicians, the software removes streak artifacts caused by arterial blood flow. It also adjusts the distribution of ...

Safeguard your infrastructure as a service (IaaS), platform as a service (PaaS), and software as a service (SaaS) resources across multicloud and hybrid environments. This form will update the search ...