Researchers have developed a new AI algorithm, called Torque Clustering, that significantly improves how AI systems independently learn and uncover patterns in data, without human guidance.

Abstract: Most clustering algorithms require setting one or more parameters, which rely on prior knowledge or are constantly adjusted based on external indicators. To address the issues of requiring ...

Introduction: Automated apple harvesting is hindered by clustered fruits, varying illumination, and inconsistent depth perception in complex orchard environments. While deep learning models such as ...

A vast region of our solar system, called the Kuiper belt, stretches from the orbit of Neptune out to 50 or so astronomical units (AU), where an AU is the distance between Earth and the sun. This ...

Is your feature request related to a problem? Please describe. The cluster graphical representations in resources page is currently a modal over the resources pages, w/o direct URL to get this modal ...

Introduction: In unsupervised learning, data clustering is essential. However, many current algorithms have issues like early convergence, inadequate local search capabilities, and trouble processing ...

I’ve observed an unexpected result when comparing direct clustering using CD-HIT at 40% threshold versus hierarchical clustering down to 30%. Direct clustering (-c 0.4): I have directly used cd-hit to ...

Community driven content discussing all aspects of software development from DevOps to design patterns. Amazon Elastic Kubernetes Service (EKS) is a managed Kubernetes service from AWS that allows ...

Roffi M, Patrono C, Collet JP, Mueller C, Valgimigli M, Andreotti F, Bax JJ, Borger MA, Brotons C, Chew DP, Gencer B, Hasenfuss G, Kjeldsen K, Lancellotti P, Landmesser U, Mehilli J, Mukherjee D, ...

ABSTRACT: Predicting the material stability is essential for accelerating the discovery of advanced materials in renewable energy, aerospace, and catalysis. Traditional approaches, such as Density ...