Multiclass Image Classification Based on Quantum-Inspired Convolutional Neural Network

• DOI: 10.32782/cmis/3392-15
• Publication Date: 2023-05-19T09:28:41Z
• Authors: Hamza Kamel Ahmed; Baraa Tantawi; Gehad Ismail Sayed
• Keywords: Multiclass classification; Contextual image classification

Multiclass image classification is considered a challenging task in computer vision that requires correctly classifying an into one of the multiple distinct groups.In recent years, quantum machine learning has emerged as topic significant interest among researchers.Using concepts such superposition and entanglement, algorithms provide more efficient method processing high-dimensional data.This paper proposes new model using quantum-inspired convolutional neural network architecture or, shortly, QCNN.The proposed consists two main phases; pre-processing based on QCNN phase.Seven benchmark datasets with different characteristics are adopted to evaluate performance model.The experimental results revealed outperformed its classical version.Additionally, demonstrated effectiveness compared state-of-the-art models.