Cong Kha Nguyen

Research Fellow @ RMIT University | Machine Learning

Cong Kha Nguyen, a research fellow at RMIT University, has been actively contributing to the field of machine learning. His research interests span machine learning, computer vision, and natural language processing. Dr. Kha earned his Ph.D. in computer science from the Tokyo University of Agriculture and Technology in March 2020. Prior to joining RMIT, he worked as a computer vision engineer at Hitachi.

Selected publications

  • Honda, M., Nguyen, H. T., Nguyen, C. T., Nguyen, C. K., Odate, R., Kanemaru, T., & Nakagawa, M. (2023, August). Incremental Teacher Model with Mixed Augmentations and Scheduled Pseudo-label Loss for Handwritten Text Recognition. In International Conference on Document Analysis and Recognition (pp. 287-301). Cham: Springer Nature Switzerland.
  • Honda, M., Nguyen, H. T., Nguyen, C. T., Nguyen, C. K., Odate, R., Kanemaru, T., & Nakagawa, M. (2023). A Semi-Supervised Learning Framework using Mixed Augmentations and Scheduled Pseudo-Label Loss for Handwritten Text Recognition. IEICE Technical Report; IEICE Tech. Rep., 122(404), 199-204.
  • Nguyen, C., & Odate, R. (2022). U.S. Patent Application No. 17/714,322.
  • Nguyen, K. C., Odate, R., & Takashi, K. (2022, September). A Robust Text Image Recognition Model with Domain Adaptation and Attention Mechanisms. In 2022 International Conference on Wavelet Analysis and Pattern Recognition (ICWAPR) (pp. 7-12). IEEE.
  • Nguyen, K. C., & Odate, R. (2021). A High Accuracy Text Detection Model of Newly Constructing and Training Strategies. In ICPRAM (pp. 635-642).
  • Nguyen, K. C., Nguyen, C. T., & Nakagawa, M. (2020, September). A semantic segmentation-based method for handwritten Japanese text recognition. In 2020 17th International Conference on Frontiers in Handwriting Recognition (ICFHR) (pp. 127-132). IEEE.
  • Nguyen, K. C., Nguyen, C. T., & Nakagawa, M. (2020). Nom document digitalization by deep convolution neural networks. Pattern Recognition Letters, 133, 8-16.
  • Nguyen, K. C., Nguyen, C. T., Hotta, S., & Nakagawa, M. (2019, September). A character attention generative adversarial network for degraded historical document restoration. In 2019 International Conference on Document Analysis and Recognition (ICDAR) (pp. 420-425). IEEE.
  • Ly, N. T., Nguyen, K. C., Nguyen, C. T., & Nakagawa, M. (2019). Recognition of anomalously deformed kana sequences in Japanese historical documents. IEICE TRANSACTIONS on Information and Systems, 102(8), 1554-1564.
  • Nguyen, K. C., Nguyen, C. T., & Nakagawa, M. (2017). A segmentation method of single-and multiple-touching characters in offline handwritten japanese text recognition. IEICE TRANSACTIONS on Information and Systems, 100(12), 2962-2972.