Hybrid Quantum–Classical Neural Networks for Efficient MNIST Binary Image Classification
Hybrid Quantum–Classical Neural Networks for Efficient MNIST Binary Image Classification
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Basel: MDPI AG
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English
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Basel: MDPI AG
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Image classification is a fundamental task in deep learning, and recent advances in quantum computing have generated significant interest in quantum neural networks. Traditionally, Convolutional Neural Networks (CNNs) are employed to extract image features, while Multilayer Perceptrons (MLPs) handle decision making. However, parameterized quantum c...
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Hybrid Quantum–Classical Neural Networks for Efficient MNIST Binary Image Classification
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TN_cdi_doaj_primary_oai_doaj_org_article_8ed1ec81c3de434f92dd44e268a7970e
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https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_8ed1ec81c3de434f92dd44e268a7970e
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ISSN
2227-7390
E-ISSN
2227-7390
DOI
10.3390/math12233684
