SANTA CLARA, CA - November 13, 2025 - - As machine learning (ML) systems become increasingly central to industries worldwide, ...

Prevailing AI architectures are not moving the needle. We need new ideas. Google Research proposes NL (nested learning). Here ...

A research team has developed a powerful computational tool—the Algorithmic Root Trait (ART) extraction method—that can “see” beyond human perception to uncover hidden features in plant roots.

Abstract: Revealing the latent low-dimensional geometric structure of high-dimensional data is a crucial task in unsupervised representation learning. Traditional manifold learning, as a typical ...

Abstract: We introduce a fully unsupervised framework designed to reconstruct X-ray CT images from truncated projections without requiring prior truncation correction. By incorporating a Radon ...

Objectives: This study aims to investigate the efficacy of unsupervised machine learning algorithms, specifically the Gaussian Mixture Model (GMM), K-means clustering, and Otsu automatic threshold ...

ABSTRACT: Purpose: The purpose of this study is to develop a scalable, risk-aware artificial intelligence (AI) framework capable of detecting financial fraud in high-throughput digital transaction ...

The objective of this work is to determine the true owner of a land—public or private—in the region of Kumasi (Ghana). For this purpose, we applied different machine learning methods to the ZEF ...

1 Johns Hopkins University Applied Physics Laboratory, Laurel, MD, United States 2 Southwest Research Institute, San Antonio, TX, United States Our methodology demonstrates a proof of concept of the ...

Summary: New research reveals that the brain may be learning even during unstructured, aimless exploration. By recording activity in tens of thousands of neurons, scientists found that the visual ...