Apply Random Quantum Neural Network on Noisy Medical Image Recognition_QIAO

Project Name:

Apply Random Quantum Neural Network on Noisy Medical Image Recognition

Team Name:

QIAO

Which challenges would you like to submit your project for?

Hybrid Quantum-Classical Computing Challenge
Quantum computing today!
NVIDIA Challenge
Amazon Braket Challenge

Power-Up plan:

NVIDIA : Encoding medical images and run QML circuit needs more than 10 qubits, which could be very slow. We need GPU computational power to speed up the coding process that could be slow in available simulators.
AWS: Amazon Braket supports several quantum platforms. Specifically, IonQ has the advantage of long coherence which is required for our project to train a Randon Quantum Neural Network.

Project Link:

https://github.com/YuNariai/project_QIAO

Access to power ups:

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We allow Xanadu Quantum Technologies to share our email addresses with the Power-Up Sponsors for the purpose of facilitating the delivery of the Power-Ups.

Yes

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This is because the account ID is needed to give the power up. If you do not have a credit card, please contact AWS to find alternative access options. Yes

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(If applying for IBM’s dedicated slots) We have obtained an IBM ID

XanaduAI / QHack2023