Abstract: Deep learning (DL) models have seen extensive application across diverse fields. As these models continue to advance for enhanced predictive capabilities, instances of performance ...

ABSTRACT: Facing increased energy demand which surpasses national grid supply capacity due to rapid population growth, urbanization, and economic activities, developing countries such as Cameroon are ...

Learn how DenseNet works and why it’s a powerful architecture in deep learning. This tutorial breaks down DenseNet’s key concepts, including dense connections, feature reuse, and parameter efficiency ...

Deep neural networks (DNNs), the machine learning algorithms underpinning the functioning of large language models (LLMs) and other artificial intelligence (AI) models, learn to make accurate ...

Objective: To explore the value of combined radiomics and deep learning models using different machine learning algorithms based on mammography (MG) and magnetic resonance imaging (MRI) for predicting ...

Abstract: The primary intent of the present research was to design and execute an electrical load forecasting system using machine learning techniques. Implementing an advanced predictive method, ...

This perspective article investigates the potential of applying artistic or “humanistic” data visualization to improve the understanding of learner’s growth in the context of highly dynamic, ...