This study presents a valuable application of a video-text alignment deep neural network model to improve neural encoding of naturalistic stimuli in fMRI. The authors found that models based on ...

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A new study led by researchers from the Yunnan Observatories of the Chinese Academy of Sciences has developed a neural network-based method for large-scale celestial object classification ...

For decades, scientists have looked to light as a way to speed up computing. Photonic neural networks—systems that use light instead of electricity to process information—promise faster speeds ...

The latter network is meant to be the standard Fully Connected Layer that is included as the final stage of a typical Convolutional Neural Network (CNN), after which a Soft Max function does the final ...

This repository contains two separate notebooks for image classification tasks using the MNIST and CIFAR-10 datasets. These notebooks leverage PyTorch to implement Convolutional Neural Networks (CNNs) ...

This study evaluates the performance and reliability of a vision transformer (ViT) compared to convolutional neural networks (CNNs) using the ResNet50 model in classifying lung cancer from CT images ...