Classification and reconstruction for single-pixel imaging with classical and quantum neural networks

Researchers used single-pixel imaging combined with classical and quantum neural networks to classify and reconstruct images from datasets like MNIST and FashionMNIST, achieving competitive accuracy rates. The study highlights that while both approaches perform well, classical methods slightly outperform quantum methods in image reconstruction tasks currently.

Read the full article at arXiv cs.LG (ML)

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