Abstract: Machine learning (ML) models were used to determine the moisture content (MC) for multiple grains and seeds after training on a large dataset obtained through several decades of research.

Introduction The proliferation of deepfake technology, synthetic media generated using advanced artificial intelligence techniques, has emerged as a ...

Abstract: This study presents a comprehensive benchmarking of 33 machine learning (ML) algorithms for bearing fault classification using vibration data, with a focus on real-world deployment in ...

Unsupervised learning is a branch of machine learning that focuses on analyzing unlabeled data to uncover hidden patterns, structures, and relationships. Unlike supervised learning, which requires pre ...

Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions or values from labeled historical data, enabling precise signals such as ...