Latest Research Updates on Quantum Computing in Smart Tech

Quantum computing is a cutting-edge field that holds tremendous potential for revolutionizing smart technologies as we know them. In recent years, research in this area has been making significant strides towards unlocking the power of quantum computing in various applications.

Here is a list of recent articles on Quantum Deep Learning, especially on hybrid quantum-classical deep neural networks.

1. Fan, F., Shi, Y., Guggemos, T., & Zhu, X. X. (2023). Hybrid quantum-classical convolutional neural network model for image classification. IEEE transactions on neural networks and learning systems.

2. Caro, M.C., Huang, HY., Ezzell, N. et al. Out-of-distribution generalization for learning quantum dynamics. Nature Communications 14, 3751 (2023). https://doi.org/10.1038/s41467-023-39381-w

3. Hafeez, M. A., Munir, A., & Ullah, H. (2024). H-QNN: A Hybrid Quantum–Classical Neural Network for Improved Binary Image Classification. AI, 5(3), 1462-1481. https://doi.org/10.3390/ai5030070

4. Sinha, B. B., Sinha, R., & Priye, V. (2025). Beyond classical approaches: redefining the landscape of high-accurate movie recommendation using QNN. The Journal of Supercomputing, 81(1), 347.

5. **Rishiwal, V., Agarwal, U., Yadav, M., Tanwar, S., Garg, D., & Guizani, M. (2025). A New Alliance of Machine Learning and Quantum Computing: Concepts, Attacks, and Challenges in IoT Networks. IEEE Internet of Things Journal.

6. **Ruan, B., Liu, Z., & Li, X. A Novel Classical-Quantum Transfer Learning Framework for Image Recognition. Available at SSRN 4806924.

7. Çavşi Zaim, H., Yılmaz, M., & Yolaçan, E. N. (2024). Design of gender recognition system using quantum-based deep learning. Neural Computing and Applications, 36(4), 1997-2014.

8. Roh, E. J., Baek, H., Kim, D., & Kim, J. (2024). Fast quantum convolutional neural networks for low-complexity object detection in autonomous driving applications. IEEE Transactions on Mobile Computing.

9. Piperno, S., Lavagna, L., De Falco, F., Ceschini, A., Rosato, A., Windridge, D., & Panella, M. (2024). Quantum Enhanced Knowledge Distillation. In Proceedings of Quantum Techniques in Machine Learning (QTML 2024) (pp. 1-3).

10. Roh, E. J., Shim, J. Y., Kim, J., & Park, S. (2025). Hybrid quantum-classical 3D object detection using multi-channel quantum convolutional neural network. The Journal of Supercomputing, 81(3), 1-24.

11. Hasan, M. J., & Mahdy, M. R. C. (2023). Bridging Classical and Quantum Machine Learning: Knowledge Transfer From Classical to Quantum Neural Networks Using Knowledge Distillation. arXiv preprint arXiv:2311.13810.

12. S. S. Reka, H. L. Karthikeyan, A. J. Shakil, P. Venugopal and M. Muniraj, "Exploring Quantum Machine Learning for Enhanced Skin Lesion Classification: A Comparative Study of Implementation Methods," in IEEE Access, vol. 12, pp. 104568-104584, 2024, doi: 10.1109/ACCESS.2024.3434681.

13. A. Khatun, M. Usman, Quantum Transfer Learning with Adversarial Robustness for Classification of High-Resolution Image Datasets. Adv Quantum Technol. 2025, 8, 2400268. https://doi.org/10.1002/qute.202400268

14. Pan, H., Zhu, X., Atici, S. F., & Cetin, A. (2023, July). A hybrid quantum-classical approach based on the hadamard transform for the convolutional layer. In International Conference on Machine Learning (pp. 26891-26903). PMLR.

15. Zaman, K., Ahmed, T., Kashif, M., Hanif, M. A., Marchisio, A., & Shafique, M. (2024). Studying the Impact of Quantum-Specific Hyperparameters on Hybrid Quantum-Classical Neural Networks. arXiv preprint arXiv:2402.10605.

16. Moussa, C., Patel, Y. J., Dunjko, V., Bäck, T., & van Rijn, J. N. (2024). Hyperparameter importance and optimization of quantum neural networks across small datasets. Machine Learning, 113(4), 1941-1966.

17. Wang, A., Hu, J., Zhang, S., & Li, L. (2024). Shallow hybrid quantum-classical convolutional neural network model for image classification. Quantum Information Processing, 23(1), 17.

18. Ren, C., Yan, R., Zhu, H., Yu, H., Xu, M., Shen, Y., ... & Kwek, L. C. (2023). Towards quantum federated learning. arXiv preprint arXiv:2306.09912.

19. Zhu, Y., Bouridane, A., Celebi, M. E., Konar, D., Angelov, P., Ni, Q., & Jiang, R. (2024). Quantum face recognition with multi-gate quantum convolutional neural network. IEEE Transactions on Artificial Intelligence.

20. Fan, F., Shi, Y., & Zhu, X. X. (2024). Land Cover Classification From Sentinel-2 Images With Quantum-Classical Convolutional Neural Networks. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

21. Fan, F., Shi, Y., Guggemos, T., & Zhu, X. X. (2025). Hybrid Quantum Deep Learning With Superpixel Encoding for Earth Observation Data Classification. IEEE Transactions on Neural Networks and Learning Systems.

22. Oviesi, S., & Tarokh, M. J. (2025). Quantum neural network-assisted learning for small medical datasets: a case study in emphysema detection. The Journal of Supercomputing, 81(1), 1-32.

23. Guha, D., Mitra, S., Kuiry, S., & Das, N. (2024). An ensemble framework approach of hybrid Quantum convolutional neural networks for classification of breast cancer images. arXiv preprint arXiv:2409.15958.

24. Sünkel, L., Altmann, P., Köle, M., & Gabor, T. (2024, September). On the Quantum Impact in Hybrid Classical-Quantum Transfer Learning. In 2024 IEEE International Conference on Quantum Computing and Engineering (QCE) (Vol. 2, pp. 11-15). IEEE.

25. Egginger, S., Sakhnenko, A., & Lorenz, J. M. (2024). A hyperparameter study for quantum kernel methods. Quantum Machine Intelligence, 6(2), 44.

26. Senokosov, A., Sedykh, A., Sagingalieva, A., Kyriacou, B., & Melnikov, A. (2024). Quantum machine learning for image classification. Machine Learning: Science and Technology, 5(1), 015040.

27. Baker, J. S., Park, G., Yu, K., Ghukasyan, A., Goktas, O., & Radha, S. K. (2024). Parallel hybrid quantum-classical machine learning for kernelized time-series classification. Quantum Machine Intelligence, 6(1), 18.

28. Domingo, L., Chehimi, M., Banerjee, S., Yuxun, S. H., Konakanchi, S., Ogunfowora, L., ... & Johnson, C. (2024, September). A hybrid quantum-classical fusion neural network to improve protein-ligand binding affinity predictions for drug discovery. In 2024 IEEE International Conference on Quantum Computing and Engineering (QCE) (Vol. 2, pp. 126-131). IEEE.

29. Bowles, J., Ahmed, S., & Schuld, M. (2024). Better than classical? the subtle art of benchmarking quantum machine learning models. arXiv preprint arXiv:2403.07059.

30. Phukan, A., Pal, S., & Ekbal, A. (2024). Hybrid Quantum-Classical Neural Network for Multimodal Multitask Sarcasm, Emotion, and Sentiment Analysis. IEEE Transactions on Computational Social Systems.