Optical computing has emerged as a powerful approach for high-speed and energy-efficient information processing. Diffractive ...

Since 2021, Korean researchers have been providing a simple software development framework to users with relatively limited ...

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 ...

AI bots told to act as trading agents in simulated markets engaged in pervasive collusion, raising new questions about how ...

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 ...

ABSTRACT: Clustering is an unsupervised machine learning technique used to organize unlabeled data into groups based on similarity. This paper applies the K-means and Fuzzy C-means clustering ...

The emergence of using Machine Learning Techniques in software testing started in the 2000s with the rise of Model-Based Testing and early bug prediction models trained on historical defect data. It ...