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 ...

Key considerations for discovery in AI-focused intellectual property (IP) litigation, including an examination of a ...

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 ...

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 ...