This innovative optical system encodes data as holograms, utilizing neural networks for decryption, paving the way for ...

As the name suggests, neural networks are inspired by the brain. A neural network is designed to mimic how our brains work to recognize complex patterns and improve over time. Neural networks ...

Deep neural networks (DNNs) are a class of artificial neural networks (ANNs) that are deep in the sense that they have many layers of hidden units between the input and output layers. Deep neural ...

This article establishes a neural network-based technique for automatic peak picking in 2D NMR spectroscopy, demonstrating a better-performing algorithm than earlier approaches in TopSpin and ...

This transformative framework taps into neural network learning patterns to correct ambiguous annotations, uncover hidden cell states, and enhance our understanding of health and disease. Research: ...

AI applications like ChatGPT are based on artificial neural networks that, in many respects, imitate the nerve cells in our brains. These networks are trained with vast quantities of data on ...

The new tech can also make AI tasks run during different stages of the shading process, so a smaller neural network can run in a pixel shader process without needing the entire GPU's computational ...

The present study examined psilocybin’s effects on belief confidence, neural entropy, and well-being in 11 healthy, psychedelic-naïve individuals (4 females, mean age = 42 years). The small ...

while functional networks from resting-state functional MRI can reflect the functional co-activation across the brain cortices. Graph neural networks (GNNs) promise to integrate multiple types of ...

A new neural network model from the University of Córdoba improves fiducial marker detection, addressing challenges in ...