How University of Texas Medical Branch is using AI to identify patients at high cardiovascular risk, flag for stroke and ...

Our model leverages a multi-branch convolutional neural network (CNN) architecture, incorporating the Hippopotamus Optimization (HO) algorithm and multiclass support vector machines (SVMs) for ...

This repository demonstrates a simple and effective implementation of a Convolutional Neural Network (CNN) using PyTorch to classify handwritten digits from the MNIST dataset. The project is ...

One notable missing feature in most ANN models is top-down feedback, i.e. projections from higher-order layers to lower-order layers in the network. Top-down feedback is ubiquitous in the brain, and ...

By incorporating a convolutional attention module, the model's capacity to learn the features of celestial sources in dense star fields is augmented. Furthermore, to more effectively manage the ...

This project is an AI-powered Security Information and Event Management (SIEM) system designed for real-time threat detection and response. Using Convolutional Neural Networks (CNN), Natural Language ...

Hefei National Research Center for Physical Sciences at the Microscale, Department of Physics, and CAS Key Laboratory of Strongly-Coupled Quantum Matter Physics, University of Science and Technology ...

Laboratory of Mathematics and Complex Systems (Ministry of Education of China), School of Mathematical Sciences, Beijing Normal University, Beijing, P. R. China ...

For clinical aid that can be applied to any patient, an automatic cross-patient epilepsy seizure detection algorithm ... artificial neural networks (ANNs). We propose an EEG-based spiking neural ...