Signature neural patterns may help predict recovery from traumatic brain injury

After traumatic brain injury (TBI), some patients may recover completely, while others retain severe disabilities. Accurately ...
IEEE

Evaluating Generative Adversarial Networks Performance in Image Synthesis with Graphical Analysis of Loss Functions and Quality Metrics

Abstract: Generative Adversarial Networks (GANs) have revolutionized image synthesis by using two neural networks, a generator and a discriminator, to create realistic images from random noise. In ...

Structural findings reveal how distinct GPCR ligands create different levels of activation

G-protein coupled receptors (GPCRs) are proteins triggered by ligands (protein-binding chemicals) from outside cells to ...
Drives & Controls

Neural networks halve distance measurement errors

The German sensor-maker Leuze claims that it has been able to cut measurement errors in demanding industrial applications by ...
WinBuzzer

Gemma Scope 2: New Google Tools Let Researchers Trace AI ‘Thought’ Circuits

Gemma Scope 2,is a comprehensive open-source suite trained on 110 petabytes of data to map internal reasoning circuits across ...
Learn With Jay on MSN

Neural network activation functions explained simply

Confused about activation functions in neural networks? This video breaks down what they are, why they matter, and the most common types — including ReLU, Sigmoid, Tanh, and more! #NeuralNetworks #Mac ...

Interpretable neural networks help reveal the nature of dark matter

A research team from the Xinjiang Astronomical Observatory (XAO) of the Chinese Academy of Sciences has developed an ...
IEEE

Nonlinear Activation Functions are Not Necessary: A Lightweight Nonlinear Activation Free Network Based on Multiscale Large Kernel Attention Mechanism for Fault Diagnosis

Abstract: In recent years, there has been a notable advancement in the field of fault diagnosis, with the introduction of Transformers and convolutional neural networks (CNNs). These two approaches ...