Faster quantum computers can learn from their own mistakes

Quantum computers promise to solve problems that would take even the fastest conventional supercomputers a vast amount of ...
Tech Xplore

Self-driving cars: Near-miss driving data can expedite AV algorithm training

The safety performance of autonomous vehicle (AV) algorithms is boosted by 90% using simulation data that better incorporates ...
IEEE

Development of a Conditional Generative Adversarial Network Model for Television Spectrum Radio Environment Mapping

Abstract: To efficiently use the finite wireless communication resource (radio spectrum), a Radio Environment Map (REM) is needed to monitor, analyse and provide rich awareness of spectrum activities ...
Psychology Today

Brain-Computer Interfaces Boosted by Novel AI Algorithm

The rise of artificial intelligence (AI) deep learning algorithms is helping to accelerate brain-computer interfaces (BCIs). Published in this month’s Nature Neuroscience is new research that shows ...
IEEE

Semantic Analysis System to Recognize Moving Objects by Using a Deep Learning Model

Abstract: This study focuses on enhancing the accuracy and efficiency of semantic analysis systems for recognizing moving objects within video sequences. The primary aim is to improve object detection ...
GitHub

SMOTE-variants for imbalanced learning

The package implements 86 variants of the Synthetic Minority Oversampling Technique (SMOTE). Besides the implementations, an easy to use model selection framework is supplied to enable the rapid ...
Frontiers

Machine Learning Algorithm Using Electronic Chart-Derived Data to Predict Delirium After Elderly Hip Fracture Surgeries: A Retrospective Case-Control Study

Background: Elderly patients undergoing hip fracture repair surgery are at increased risk of delirium due to aging, comorbidities, and frailty. But current methods for identifying the high risk of ...