Binary Image Classification Using Machine Learning and Deep Quantum Neural Networks

This paper helps to explore the intricate task of natural and precise image grouping for effective organization and retrieval. High precision in image classification is challenging due to the complexity of images and the vast array of defining features. Deep learning-based artificial intelligence, a rapidly progressing field, plays a crucial role in various industries such as image classification, computer vision, text mining, voice recognition, and medical scan analysis. Deep convolutional neural networks (CNNs) excel in advanced image categorization and processing, particularly for high-resolution images. This study introduces a deep quantum neural network (QNN) technique for binary image categorization, delving into the latest research on image classification using cross-entropy functions, deep learning, and convolutional neural networks.