Demonstration for Quantum Convolutional Neural Network with Chest X-ray Pneumonia Dataset

[RiaKhatoniar008]

Title` of the quantum algorithm Demonstration for Quantum Convolutional Neural Network with Chest X-ray Pneumonia Dataset

Description of the quantum algorithm Quantum Convolutional Neural Networks (QCNNs) represent an innovative fusion of quantum computing principles with classical convolutional neural network (CNN) architectures. Unlike their classical counterparts, QCNNs harness the unique properties of quantum bits (qubits), including superposition and entanglement, to perform convolutional operations in a highly parallelized manner. These networks aim to enhance the processing capabilities of classical CNNs, particularly in tasks such as image recognition. QCNNs follow a hybrid quantum-classical approach, leveraging quantum resources for specific computations while relying on classical computing for other aspects. The integration of quantum features in QCNNs holds the potential to outperform classical counterparts in certain scenarios, though challenges such as quantum noise and error correction must be addressed to fully exploit the advantages of quantum computing in the realm of machine learning.

This page should have:

• Demonstration (Users should be able to tweak options. Show the output circuit, measurement results, and histogram to the user.)
• Detailed explanation including mathematics and examples (wherever required) divided into multiple sections.
• Generalized and modular code for the algorithm. (See the code given in Bernstein Vazirani and Deutsch Josza Algo Pages for reference).
• Links to external sources and further study material.
• About the author (small description and socials).

[devilkiller-ag]

@RiaKhatoniar008 move forward with this issue. Feel free to open a draft PR for your work.