Abstract
Image classification has an important role in many machine learning applications. Numerous classification techniques based on quantum machine learning have been reported recently. In this article, we investigate the features of the quanvolutional neural network—a hybrid quantum-classical image classification technique, which is inspired by the convolutional neural network and has the potential to outperform current image processing techniques. We improve the training strategy and evaluate the classification tasks on three traditional public datasets in terms of different topologies, sizes, and depths of filters. Finally, we propose four efficient configurations for the quanvolutional neural network to improve image classification.
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Data are available from the corresponding authors upon reasonable request. All codes used in this study are available on GitHub (https://github.com/vutuanhai237/DynamicQNN).
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Acknowledgements
The authors thank Bui Cao Doanh for a helpful discussion of the experiment’s setup in this work.
Funding
This research was supported by the VNUHCM-University of Information Technology’s Scientific Research Support Fund.
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Hai. V. T. conducted the experiments, and Bao. P. T. and Lawrence. H. L. proposed the methodology. All authors reviewed the manuscript.
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Appendix
Appendix
As mentioned in Section 2.2, the quantum compiling technique will consume large resources when dealing with a very large dataset. Thus, we can convert patches of each \(\{X_j\}\) in dataset \(\mathcal {X}\) based on filter size f, store it, and then use it later:
where \(\varvec{\theta }^{QC}_{i,j}\) is the optimal parameter in the quantum compiling process and the depth of the encoder is the depth \(U_{\text {QC}, f}\). Then, this quantum dataset can be used in various problems.
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Vu, T.H., Le, L.H. & Pham, T.B. Exploring the features of quanvolutional neural networks for improved image classification. Quantum Mach. Intell. 6, 29 (2024). https://doi.org/10.1007/s42484-024-00166-z
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DOI: https://doi.org/10.1007/s42484-024-00166-z