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Quantum Image Denoising with Machine Learning: A Novel Approach to Improve Quantum Image Processing Quality and Reliability
By training and employing a machine learning model that identifies and corrects the noise in quantum processed images, we can compensate for the noisiness caused by the machine and retrieve a processing result similar to that performed by a classical computer with higher efficiency.
Implementation of The Future of Drug Discovery: QuantumBased Machine Learning Simulation (QMLS)
This paper is based on our first paper, where we pitched the concept of machine learning combined with quantum simulations.
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