2022 IEEE International Conference on Quantum Computing and Engineering (QCE) 2022
DOI: 10.1109/qce53715.2022.00134
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Organ classification Using Quantum Convolution Network

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“…There have also been hybrid models with quanvolutional layers in the network where we undertake local transformation of the data with several random quantum circuits in the set bounded-error quantum polynomial time (150). Recently, quanvolutional methods were used for physiological application such as for body part recognition using Hybrid Quantum Convolutional Neural Networks, although in this case the classical counterpart was found to have a greater validation accuracy by 0.5% (151).…”
Section: Quantum Reinforcement Learning and Deep Learningmentioning
confidence: 99%
“…There have also been hybrid models with quanvolutional layers in the network where we undertake local transformation of the data with several random quantum circuits in the set bounded-error quantum polynomial time (150). Recently, quanvolutional methods were used for physiological application such as for body part recognition using Hybrid Quantum Convolutional Neural Networks, although in this case the classical counterpart was found to have a greater validation accuracy by 0.5% (151).…”
Section: Quantum Reinforcement Learning and Deep Learningmentioning
confidence: 99%