Methods: This paper introduces DMSACNN, an end-to-end deep multiscale attention convolutional neural network for MI/ME-EEG decoding. DMSACNN incorporates a deep multiscale temporal feature extraction ...

AI is revolutionizing transportation fault detection by enabling real-time monitoring, pattern recognition, and proactive ...

Traditional MRI analysis requires significant time and expertise, often leading to diagnosis and treatment planning delays.

GCN, a groundbreaking disentangled graph convolutional network that dynamically adjusts feature channels for enhanced node representation, outperforming traditional methods in node classification ...

This is the code for FCHD - A Fast and accurate head detector. See the paper for details and video for demo.

Abstract: Convolutional neural network (CNN) was widely applied to the data-driven based fault diagnosis. However, it often needs to artificially transform the signal into a two-dimensional (2D) image ...

The ability to predict outcomes and trends can mean the difference between thriving and merely surviving. Enter artificial ...

Introduction The era of machine learning is changing day by day, and innovation is being directed by open-source libraries.

Researchers from Faridpur Engineering College, Bangladesh, developed AI-driven models to automate mango ripeness ...

The following is a summary of “Computer-aided diagnosis based on 3D deep convolutional neural network system using novel 3D ...

AMD's latest FidelityFX Super Resolution (FSR) 4 incorporates AI, but will be exclusive for RDNA 4 graphics cards ...

AMD Image Inspector is a new AI model that will capture screenshots while you play to check for issues that might need ...