“Over the past decade, deep-learning-based representations have demonstrated remarkable performance in academia and industry. The learning capability of convolutional neural networks (CNNs) originates ...

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, ...

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.

You can 3D-print nearly anything: rockets, mouse ovaries, and for some reason, lamps made of orange peels. Now, scientists at Monash University in Melbourne, Australia, have printed living neural ...

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 ...

Relief-type cultural heritage objects are commonly found in many historical sites worldwide, but often suffer from varying levels of damage and deterioration. Traditional methods for image ...

A research team has developed a powerful unsupervised deep learning network that can accurately separate wood and leaf components in 3D point clouds of trees—without the need for labor-intensive data ...

The innovative multi-task neural network achieves simultaneous depth estimation and soft-edge detection in a single network, producing clear 3D reconstructed images of relief-type cultural heritage ...

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 ...

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 ...