Department of Chemical and Biochemical Engineering, Laboratory of Equipment Design, TU Dortmund University, Emil-Figge-Str. 68, 44227 Dortmund, Germany Article Views are the COUNTER-compliant sum of ...

When it comes to tasks other than number crunching, the human brain possesses many advantages over a digital computer. We can quickly recognize a face, even when seen from the side in bad lighting in ...

This research presents a Driver Drowsiness Detection System (DDDS) that uses a Convolutional Neural Network (CNN) to improve road safety. The system uses a vast dataset of 97,860 images from the ...

This article will take you from an empty Python file to creating, compiling, and training a neural network using TensorFlow and Keras — without drowning you in heavy math. Building a Model: How to ...

There are many stories of how artificial intelligence came to take over the world, but one of the most important developments is the emergence in 2012 of AlexNet, a neural network that, for the first ...

Large language models evolved alongside deep-learning neural networks and are critical to generative AI. Here's a first look, including the top LLMs and what they're used for today. Large language ...

AI thrives on data but feeding it the right data is harder than it seems. As enterprises scale their AI initiatives, they face the challenge of managing diverse data pipelines, ensuring proximity to ...

To navigate the world around us, we can use different actions, such as walking, swimming, or climbing. How does our brain compute and represent such locomotive action affordances? Here, we show that ...

In this article, we explore how to build a simple feed forward neural network in C to recognize handwritten digits from the MNIST dataset. The network consists of an input layer, a hidden layer, and ...

Entanglement in proteins is a fascinating structural motif that is neither easy to detect via traditional methods nor fully understood. Recent advancements in AI-driven models have predicted that ...

This repository contains an implementation of a graph neural network for the segmentation and object detection in radar point clouds. As shown in the figure below, the model architecture consists of ...