Neuroscientists want to understand how individual neurons encode information that allows us to distinguish objects, like ...

Steven Brightfield, Chief Marketing Officer at BrainChip, about neuromorphic computing and its Akida spiking neural network ...

How reliable is artificial intelligence, really? An interdisciplinary research team at TU Wien has developed a method that ...

Image restoration is a critical task in low-level computer vision, aiming to restore high-quality images from degraded inputs. Various models, such as convolutional neural networks (CNNs), generative ...

Deep learning models, such as convolutional neural networks (CNNs) and recurrent neural networks (RNNs) are designed to partly emulate the functioning and structure of biological neural networks. As a ...

Artificial intelligence (AI) models remain an emerging strategy to accelerate materials design and development. We demonstrate that CNN models can characterize DNA origami nanostructures employed in ...

Artist Terence Broad makes AI produce images without any training data at all.

Recently, convolutional neural networks (CNN) have been widely used in image denoising. But with most CNN denoising methods, all the channels are treated equally and the relationship between spatial ...

AI is now a part of our everyday lives. From the massive popularity of ChatGPT to Google cramming AI summaries at the top of ...

In this paper, we study the effect of three different quantum image encoding approaches on the performance of a convolution-inspired hybrid quantum-classical image classification algorithm called ...

This function detects SIFT corner points in a grayscale image, computes their centroid, and finds the pixels farthest and nearest to it. Input: 2D matrix I of grayscale image, scalar ...

Thanks to the neural network, the researchers now suspect, for example, that the black hole at the center of the Milky Way is spinning almost at top speed. Its rotation axis points to Earth.