bsiegelwax/784-Dimensional-Quantum-MNIST
Quantum MNIST using amplitude encoding instead of dimensionality reduction.
This project helps quantum computing researchers and enthusiasts explore new ways to classify image data. It takes standard MNIST handwritten digit images and processes them using a quantum circuit that preserves the full image data. The output is a classification of the digit.
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Use this if you are researching quantum machine learning and want to experiment with amplitude encoding for image classification without dimensionality reduction.
Not ideal if you are looking for a practical, ready-to-deploy image classification solution for classical computers or a quantum solution that prioritizes simplified data representation.
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Last pushed
Dec 09, 2021
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