Agriculture has undergone progressive transformations using ever-evolving technologies to
increase productivity and profitability. A new approach to agricultural management based on …

This paper introduces the Hybrid Quantum Deep Neural Network (HQDNN), a pioneering
model that amalgamates classical Convolutional Neural Network (CNN) architecture with …

By utilizing hybrid quantum–classical neural networks (HNNs), this research aims to
enhance the efficiency of image classification tasks. HNNs allow us to utilize quantum …

A problem related to the development of a supervised learning method for recurrent spiking
neural networks is addressed in the paper. The widely used Leaky-Integrate-and-Fire model …

Image classification is typically a research area that trains an algorithm for accurately
identifying subjects in images that have never been seen before. Training a model to …

Recently, quantum machine learning has been ap-plied to stochastic-based modelling,
promising that the inherent uncertainty in quantum computing will be a significant advan …

With the development of the economy and science, information technology has become
increasingly integrated into modern life, making information encryption crucial. The …

In emotion classification using facial expressions, noise in the data is the main factor
hindering improvement in accuracy. In this study, a deep learning model was developed that …

The complex and nonlinear nature of brain tumor morphology and texture pose significant
challenges for representative feature extraction from magnetic resonance imaging (MRI) …

At the intersection of quantum computing and machine learning, this review paper explores
the transformative impact these technologies are having on the capabilities of data …