What are convolutional neural networks in deep learning? Convolutional neural networks are used in computer vision tasks, which employ convolutional layers to extract features from input data.

The world of artificial intelligence (AI) is rapidly evolving, and AI is increasingly enabling applications that were previously unattainable or very difficult to implement. A subsequent article, ...

Learn about the most prominent types of modern neural networks such as feedforward, recurrent, convolutional, and transformer networks, and their use cases in modern AI. Neural networks are the ...

Ultralytics Inc., a developer of computer vision models, today announced that it has raised $30 million in funding. Elephant ...

WiMi Hologram Cloud Inc. (NASDAQ: WiMi) ("WiMi" or the "Company"), a leading global Hologram Augmented Reality ("AR") Technology provider, today announced that they are actively exploring Scalable ...

New data reveals advances in tiny neural network performanceSAN FRANCISCO, Sept. 17, 2025 (GLOBE NEWSWIRE) -- Today, ...

This paper proposes a deep learning framework F-GCN that integrates multiple wavelet bases, and extracts MI brain electrical ...

Machine Learning Models Using Routinely Collected Clinical Data Offer Robust and Interpretable Predictions of 90-Day Unplanned Acute Care Use for Cancer Immunotherapy Patients Whole-slide images (WSIs ...

Scientists have created a novel probabilistic model for 5-minutes ahead PV power forecasting. The method combines a convolutional neural network with bidirectional long short-term memory, attention ...

The team reported that their AI copilot solution improved performance by a factor of 3.9 times for the paralyzed participant ...