New research offers clues to what goes on inside the minds of machines as they learn to see. Instead of attempting to account for a neural network's decision-making on a post hoc basis, their method ...

Recent advancements have witnessed an impressive convergence between neural network architectures and spectroscopic techniques within computer vision. Deep learning methods, particularly convolutional ...

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.

Computer vision continues to be one of the most dynamic and impactful fields in artificial intelligence. Thanks to breakthroughs in deep learning, architecture design and data efficiency, machines are ...

In recent years, owing to the advancements in the immense processing ability and parallelism of modern graphics processing units (GPUs), deep learning based on convolutional neural networks (CNN) has ...

Computer vision, or the ability of artificially intelligent systems to “see” like humans, has been a subject of increasing interest and rigorous research for decades now. As a way of emulating the ...

Head over to our on-demand library to view sessions from VB Transform 2023. Register Here Deep neural networks — layers of mathematical functions modeled after biological neurons — are a versatile ...

To researchers’ surprise, deep learning vision algorithms often fail at classifying images because they mostly take cues from textures, not shapes. When you look at a photograph of a cat, chances are ...

In brief: Someone was able to achieve remarkable results in upscaling a very old, low-resolution, black and white video from 1896 to a crystal-clear 4K video at 60 frames per second. This is one of ...

DURHAM, N.C. -- The artificial intelligence behind self-driving cars, medical image analysis and other computer vision applications relies on what's called deep neural networks. Loosely modeled on the ...