Neuroscientists have been trying to understand how the brain processes visual information for over a century. The development ...

The application of neural networks to halftone image processing has catalysed transformative advances in both the generation and restoration of digital images. By leveraging deep learning ...

To study how a key chemical neuromodulator affects signaling in the brain's cortex, Garrett Neske, PhD, has received a three-year, $300,000 grant from the Whitehall Foundation, a nonprofit ...

A Performant Side-channel-Resistant RISC-V Core Securing Edge AI Inference” was published by researchers at Northeastern ...

Researchers have devised a way to make computer vision systems more efficient by building networks out of computer chips’ logic gates. Networks programmed directly into computer chip hardware can ...

Neuro-symbolic AI is a unique form of artificial intelligence that combines the strengths of neural and symbolic AI architectures. This powerful AI model can model cognition, learning, and reason, ...

Key opportunities in the handwriting recognition AI market include growing demands for automated document processing, AI-powered handwriting analysis, and mobile integration. Advances in neural ...

Bridging communication gaps between hearing and hearing-impaired individuals is an important challenge in assistive technology and inclusive education. In an attempt to close that gap, I developed a ...

MicroCloud Hologram Inc. (NASDAQ: HOLO), ("HOLO" or the "Company"), a technology service provider, released learnable quantum spectral filter technology for hybrid graph neural networks. This ...