Digital image processing domain is growing day-by-day by introducing novel technologies
to provide assistance for several applications such as robotic activities, underwater network …

Extreme learning machine (ELM), a randomized learning paradigm for single hidden layer
feed-forward network, has gained significant attention for solving problems in diverse …

Neural networks constitute a well-established design method for current and future
generations of artificial intelligence. They depends on regressed arithmetic between …

An enormous number of CNN classification algorithms have been proposed in the literature.
Nevertheless, in these algorithms, appropriate filter size selection, data preparation …

Abstract In Artificial Intelligence, the machine modeling technique means to behave in the
manner of human reflects indistinguishable. To automatizes the development of rational …

In recent years, the non-handcrafted feature extraction methods have gained increasing
popularity for solving pattern classification tasks due to their inherent ability to extract robust …

Federated Learning (FL) has emerged as a fundamental learning paradigm to harness
massive data scattered at geo-distributed edge devices in a privacy-preserving way. Given …

This study introduces an innovative approach to image classification that uses Gaussian
copulas with an Empirical Cumulative Distribution Function (ECDF) approach. The strategic …

As we enter the 21st century, with the rapid development of information technology and
advanced manufacturing technology and the rapid development of intelligent manufacturing …

The MNIST dataset is considered a challenging problem for machine learning algorithms.
The present paper introduces a novel approach based on a truncated SVD and kernel …