QUANTUM COMPUTING: IMAGE CLASSIFICATION AND VISUALIATION SYSTEM

QUANTUM COMPUTING: IMAGE CLASSIFICATION AND VISUALIATION SYSTEM

¹ Ms E. Padma, ²Sai Lakshmi Kailash, ³Senugala Kavya Sree

¹Assistant Professor, ²Graduate Students, ³Graduate students

 Department of Computer Science Engineering,

SCSVMV University, Enathur, India

Abstract

The system is a quantum computing based binary image classification and visualization system. It uses the principle of superposition and quantum neural network to achieve an estimated accuracy of 95.5%. The model here is trained using a quantum circuit that is built using cirq and then trained using QNN. The sole purpose of this model is to classify the images into their respective category using quantum programming. It uses principles of image classification and descaling along with python and concepts of TensorFlow. Some key technologies used are Image Classification; Image Visualization; TFQ (Tensorflow Quantum); QNN (Quantum Neural Network); Quantum Computing.

keywords: Image Classification; Image Visualization; TFQ (Tensorflow Quantum); QNN (Quantum Neural Network); Quantum Computing