With the severe economic and societal impacts of traffic crashes, proactive traffic safety management has become a key approach to reduce crash risks, and real-time crash prediction (RTCP) serves as a ...

Researchers found that spiking neural networks maintain robust EEG motor imagery decoding under heavy noise and channel loss ...

Accurate segmentation of medical images is essential for clinical decision-making, and deep learning techniques have shown remarkable results in this area. However, existing segmentation models that ...

Convolutional neural networks (CNNs) and generative adversarial networks (GANs) are examples of neural networks-- a type of deep learning algorithm modeled after how the human brain works. "GANs are ...

This project is a machine learning application built from scratch to classify images of cats and dogs using a Convolutional Neural Network (CNN) model. The dataset includes thousands of images, ...

Understanding lung infections such as pneumonia and tuberculosis requires expert analysis of chest CT scans. Catching these ...

Every neural network powering your phone's camera, the language model on your screen, and the recommendation engine choosing your next video was trained with the same four-decade-old algorithm: ...

Stephane is a tech enthusiast and AI advocate with a deep-seated passion for leveraging technology to solve real-world problems. With a background in Chemistry and hands-on experience in AI,... We ...