Machine learning reduces friction at every stage of a business, whether you’re coming up with new product ideas or getting the goods delivered to the client. It increases business efficiency, improves ...

Abstract: Machine learning has been widely applied in industrial intelligent manufacturing. However, significant domain differences in data across factories make it difficult for models trained on a ...

This project implements a zero-day attack detection system that identifies previously unknown attacks by analyzing system behavior, network patterns, and application activities. It uses unsupervised ...

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 ...

Artificial intelligence research is rapidly evolving beyond pattern recognition and toward systems capable of complex, human-like reasoning. The latest breakthrough in this pursuit comes from the ...

The Recentive decision exemplifies the Federal Circuit’s skepticism toward claims that dress up longstanding business problems in machine-learning garb, while the USPTO’s examples confirm that ...

With the development of artificial intelligence(AI) in computer science and statistics, it has been further applied to the medical field. These applications include the management of infectious ...

Foundation models, often massive neural networks trained on extensive text and image data, have significantly shifted how artificial intelligence systems handle language and vision tasks. These models ...

Supervised learning relies on historical, labeled data to train algorithms for specific outcomes. This approach is widely used in the financial sector, where reliable past data can guide future ...