Published Papers

1. T. Munyer, A. Tanvir, A. Das, and X. Zhong, "DeepTextMark: A Deep Learning-Driven Text Watermarking Approach for Identifying Large Language Model Generated Text," IEEE Access, vol. 12, p.40508-40520, 2024. (Preprint: https://arxiv.org/abs/2305.05773; code: https://github.com/tanvir097/DeepTextMark.git)

2. B. Karki, X. Zhong, Y. Chen, C. Tsai, "Interpretable Classification of Myositis from Muscle Ultrasound Images," in 2024 8th International Conference on Medical and Health Informatics (ICMHI 2024), 2024, to appear.

3. A. Das, and X. Zhong, "ViewMix: Augmentation for Robust Representation in Self-Supervised Learning," IEEE Access, vol. 12, p.8461-8470, 2024. (preprint: https://arxiv.org/abs/2309.03360)

4. HR. Ng, X. Zhong, Y. Nam, and  J-H. Youn, "Deep-Learning-Based Approach for Automated Detection of Irregular Walking Surfaces for Walkability Assessment with Wearable Sensor ," Applied Sciences, vol. 13, no. 24, p.13053, 2023. (https://doi.org/10.3390/app132413053) 

5. A. Dasgupta, and X. Zhong, "Robust Image Watermarking based on Cross-Attention and Invariant Domain Learning," in 2023 International Conference on Computational Science and Computational Intelligence, IEEE, 2023. (preprint: https://arxiv.org/abs/2310.05395)

6. X. Zhong, A. Das, F. Alrasheedi, and Abdullah Tanvir, "A Brief, In-Depth Survey of Deep Learning-Based Image Watermarking," Applied Sciences, vol. 13, no. 21, p.11852, 2023. (Preprint: https://arxiv.org/abs/2308.04603; paper: https://www.mdpi.com/2076-3417/13/21/11852) 

7. D. Panda, P. Basia, K. Nallavolu, X. Zhong, H. Siy, and M. Song, “A Statistical Method for API Usage Learning and API Misuse Violation Finding,” in 2023 IEEE/ACIS 21st International Conference on Software Engineering Research, Management and Applications (SERA), IEEE, 2023, pp. 358-365.

8. F. Alrasheedi, X. Zhong, and P. Huang, "Padding Module: Learning the Padding in Deep Neural Networks," IEEE Access, vol. 11, p.7348-7357, 2023. (preprint: https://arxiv.org/abs/2301.04608)

9. T. Munyer, D. Brinkman, X. Zhong, C. Huang, and I. Konstantzos, "Foreign Object Debris Detection from Airport Pavement Images based on Self-supervised Localization and Vision Transformer," in 2022 International Conference on Computational Science and Computational Intelligence (CSCI'22), IEEE, 2022. (paper: https://arxiv.org/abs/2210.16901; code: https://github.com/FOD-UNOmaha/FODAnomalyData; Presentation: https://youtu.be/xBKkhkSuvGE)

10. N. Khatri, A. Dasgupta, Y. Shen, X. Zhong, and F. Y. Shih, "Perspective Transformation Layer", in 2022 International Conference on Computational Science and Computational Intelligence (CSCI'22), IEEE, 2022. (paper: https://arxiv.org/abs/2201.05706; code: https://github.com/kcnishan/Perspective_Transformation_Layer)

11. Y. Shen, F. Y. Shih, X. Zhong, and I. Chang, “Deep Morphological Neural Networks,” International Journal of Pattern Recognition and Artificial Intelligence, vol. 36, no. 12, p.2252023, 2022. (paper: https://arxiv.org/abs/1909.01532)

12. A. Das and X. Zhong, "A Deep Learning-based Audio-in-Image Watermarking Scheme," in Visual Communications and Image Processing, IEEE, 2021, pp. 1-5. (paper: https://arxiv.org/abs/2110.02436; code: https://github.com/arjondas/deep-aiwm) 

13. T. Munyer, C. Huang, P. Huang, and X. Zhong, "FOD-A: A Dataset for Foreign Object Debris in Airports," in International Conference on Machine Learning and Applications, IEEE, 2021. (paper: https://arxiv.org/abs/2110.03072)

14. S. Liu, F. Y. Shih, X. Zhong, "Classification of chest X-ray images using novel adaptive morphological neural networks," International Journal of Pattern Recognition and Artificial Intelligence, vol. 35, no. 10, p.2157006 (14 pages), 2021. (paper)

15. T. Munyer, D. Brinkman, C. Huang, and X. Zhong, "Integrative Use of Computer Vision and Unmanned Aircraft Technologies in Public Inspection: Foreign Object Debris Image Collection," in DG. O2021: The 22nd Annual International Conference on Digital Government Research, 2021, pp. 437-443. (paper: https://arxiv.org/abs/2106.00161)

16. S. Liu, X. Zhong, and F. Y. Shih, "Joint learning for pneumonia classification and segmentation on medical images," International Journal of Pattern Recognition and Artificial Intelligence, vol. 35, no. 5, p.2157003 (19 pages), 2021.  (paper)

17. X. Zhong and F.Y. Shih, "Automatic Image Pixel Clustering based on Mussels Wandering Optimization," International Journal of Pattern Recognition and Artificial Intelligence, vol. 35, no. 2, p.2154005 (17 pages), 2021. (paper)

18. S. Mastorakis, X. Zhong, P. Huang, and R. Tourani, "DLWIoT: Deep Learning-based Watermarking for Authorized IoT Onboarding," in 2021 IEEE 18th Annual Consumer Communications & Networking Conference (CCNC), 2021, pp. 1-7. (paper: https://arxiv.org/abs/2010.10334)

19. X. Zhong, P. Huang, S. Mastorakis, and F. Y. Shih, "An Automated and Robust Image Watermarking Scheme Based on Deep Neural Networks," IEEE Transactions on Multimedia, vol. 23, pp. 1951-1961, 2021. (paper: https://arxiv.org/abs/2007.02460; code: https://github.com/kcnishan/DL_watermark_endtoend) 

20. D. Abeyrathna, P. Huang, and X. Zhong, "Anomaly Proposal-based Fire Detection for Cyber-Physical Systems," in 2019 International Conference on Computational Science and Computational Intelligence (CSCI), IEEE, 2019, pp. 1203-1207. (acceptance rate 17%) (paper)

21. X. Zhong and F.Y. Shih, "Robust Multibit Image Watermarking based on Contrast Modulation and Affine Rectification," International Journal of Pattern Recognition and Artificial Intelligence, vol. 33, no. 14, p.1954036, 2019.

22. X. Zhong and F.Y. Shih, "An Efficient Saliency Detection Model Based on Wavelet Generalized Lifting," International Journal of Pattern Recognition and Artificial Intelligence, vol. 33, no. 2, p.1954006, 2019. (paper)

23. X. Zhong and F.Y. Shih, "A High-Capacity Reversible Watermarking Scheme Based on Shape Decomposition for Medical Images," International Journal of Pattern Recognition and Artificial Intelligence, vol.33, no.1, p.1950001, 2019. (paper)

24. F.Y. Shih, Y. Shen and X. Zhong, "Development of Deep Learning Framework for Mathematical Morphology," International Journal of Pattern Recognition and Artificial Intelligence, vol. 33, no. 6, p. 1954024, 2019. (paper)

25. F.Y. Shih, X. Zhong, I. C. Chang and S. I. Satoh, "An Adjustable-purpose Image Watermarking Technique by Particle Swarm Optimization," Multimedia Tools and Applications, vol. 77, no.2, pp.1623-1642, 2018. (paper)

26. F.Y. Shih and X. Zhong, "Achieving Image Watermarking Robustness by Geometric Rectification," International Journal of Pattern Recognition and Artificial Intelligence, vol. 31, no.04, pp.1754007, 2017.

27. F.Y. Shih and X. Zhong, "Automated Counting and Tracking of Vehicles," International Journal of Pattern Recognition and Artificial Intelligence, vol. 31, no.12, pp.1750038, 2017.

28. F.Y. Shih and X. Zhong, "High-capacity Multiple Regions of Interest Watermarking for Medical Images," Information Sciences, vol. 367, pp.648-659, 2016. (paper)

29. F.Y. Shih and X. Zhong, "Intelligent Watermarking for High-Capacity Low-Distortion Data Embedding," International Journal of Pattern Recognition and Artificial Intelligence, vol. 30, no. 05, pp.1654003, 2016.

Others & arXiv

• B. Karki, C. Tsai, P. Huang, and X. Zhong, "Deep Learning-based Text-in-Image Watermarking," https://www.arxiv.org/abs/2404.13134  

• F. Alrasheedi, and X. Zhong, "Imperceptible Adversarial Attack on Deep Neural Networks from Image Boundary," https://arxiv.org/abs/2308.15344