The CMS Collaboration has shown, for the first time, that machine learning can be used to fully reconstruct particle ...

Beijing, Feb. 06, 2026 (GLOBE NEWSWIRE) -- WiMi Releases Hybrid Quantum-Classical Neural Network (H-QNN) Technology for Efficient MNIST Binary Image Classification ...

This video explains why the Fast Fourier Transform (FFT) is often called the most important algorithm ever created. Originally developed to help detect hidden nuclear weapons tests during the Cold War ...

The Toledo Museum of Art is proud to present Infinite Images: The Art of Algorithms, a bold and thought-provoking new exhibition that opens on Thursday, October 16 at 11am at 2445 Monroe Street. This ...

Abstract: The Satellite Internet of Things (SatIoT) enables integrated space–air–ground connectivity and information exchange through satellite communication networks and distributed sensors. Its ...

This project presents an advanced image compression system designed to enhance the standard JPEG algorithm by introducing a more perceptually-driven approach. The traditional JPEG standard relies on a ...

This article was originally published at The Conversation. The publication contributed the article to Space.com's Expert Voices: Op-Ed & Insights. Professional astronomers don’t make discoveries by ...

College of Rail Transit Locomotive and Rolling Stock, Hunan Railway Professional Technology College, Zhuzhou, China. Many people have made efforts to design and improve high-performance FIR filters, ...

John Peterson does not work for, consult, own shares in or receive funding from any company or organization that would benefit from this article, and has disclosed no relevant affiliations beyond ...

Abstract: Learning-based image compression algorithms typically focus on designing encoding and decoding networks and improving the accuracy of entropy model estimation to enhance the rate-distortion ...

ABSTRACT: In this paper, we investigate the convergence of the generalized Bregman alternating direction method of multipliers (ADMM) for solving nonconvex separable problems with linear constraints.