Do emulated quantum circuits change what CNNs look at? Performance and explainability comparison in medical image classification
Numerous studies have analyzed the use of hybrid quantum-classical convolutional neural networks as a promising alternative to classical deep learning. However, network components on quantum hardware impose fundamental limitations, while the scalability of quantum circuits leads to trainability issues. In this work, we investigate whether small, classically-emulated quantum circuit components can play a meaningful role within complex models, offering an alternative to purely classical convolutio
Record details
Published: 23 July 2026
Source: arXiv fairness query
Category: Research
Topics: Healthcare · Transparency · Finance, VC & PE
Retrieved: 27 July 2026
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ethics.ai (23 July 2026), “Do emulated quantum circuits change what CNNs look at? Performance and explainability comparison in medical image classification,” evidence record 13730, https://ethics.ai/record/13730 (originally published by arXiv fairness query).
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