Constrained deep learning is an advanced approach to training deep neural networks by incorporating domain-specific constraints into the learning process.

A collection of real-world machine learning and AI projects. Explore hands-on implementations of cutting-edge models, practical solutions, and techniques to tackle real-world challenges using AI.

With the rapid growth of the international banking industry, bank failures can lead to severe economic losses and social ...

Department of Mathematics and Sciences, College of Humanities and Sciences, Ajman University, Ajman, UAE ...

AI models learn through a process called training, where data is passed through a neural network to identify patterns. The model makes predictions, compares them to actual results, and adjusts ...

In previous study, Lien et al. (2023) investigates the use of convolutional neural networks (CNNs) to classify the severity of AD based on SPECT (single-photon emission computed tomography) images.

In the rapidly evolving fields of computer vision (CV) and machine learning (ML), both software frameworks and hardware ...

This study aims to enhance the detection of HIFs in PV-integrated systems using advanced machine learning techniques. The approach employs various classifiers, including artificial neural networks, ...