Đỗ Thanh Hà

Đỗ Thanh Hà, Doctor
Function:
Associate Dean of Faculty
Office:
T5-505
VNU mail:
hadt_tct@vnu.edu.vn
Research Fields:
Pattern Recognition and Document Image Analysis, Medical Image Processing , Optimize the computer vision algorithms in autonomous car , Machine Learning , Computer Vision
Education :
  • Doctor, 2010, Informatique, Université de Lorraine, France
  • Master, 2007, Mathematics, VNU Hanoi University of Science
  • Bachelor, 2005, Applied Mathematics and Informatics, VNU Hanoi University of Science
Teaching:
  • Image Processing
  • Programming in C/C++, Java
  • Practicum in Computing
  • Machine Learning
  • Computer Graphics
  • Computer Vision
Science Activities:
  • Program committee member of the some International Conferences
  • Reviewer and Sub-reviewer for some national journal, international conferences and international journals
Awards:
  • 2013 Sigweb DocEng Best Paper Award, Granted by ACM Symposium on Document Engineering
  • 2004 Exemplary female students in information technology
  • 2003 representative for talented and excellent young students of Vietnam National University

Publications

  1. ViHealthNLI: A Dataset for Vietnamese Natural Language Inference in Healthcare. In: Proceedings of the 3rd Annual Meeting of the Special Interest Group on Under-resourced Languages@ LREC-COLING 2024. Proceedings of the 3rd Annual Meeting of the Special Interest Group on Under-resourced Languages@ LREC-COLING 2024.; 2024. Available at: https://aclanthology.org/2024.sigul-1.48/.
  2. Deep Learning for Table Detection: A Comparative Study on Efficiency with Increased Data. In: International Workshop on ADVANCEs in ICT Infrastructures and Services. International Workshop on ADVANCEs in ICT Infrastructures and Services.; 2024. Available at: https://hal.science/hal-04723957/document.
  3. The U-ReACH Model for Ship Detection over Satellite Imagery. In: 2024 International Conference on Multimedia Analysis and Pattern Recognition (MAPR). 2024 International Conference on Multimedia Analysis and Pattern Recognition (MAPR).; 2024. Available at: https://ieeexplore.ieee.org/abstract/document/10661071.
  4. Automated Classification of Lung Injury from X-ray Images using Deep Learning Network. In: 2022 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC). 2022 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC).; 2022. Available at: https://ieeexplore.ieee.org/abstract/document/9979927.
  5. Supporting thyroid cancer diagnosis based on cell classification over microscopic images. In: 2022 International Conference on Multimedia Analysis and Pattern Recognition (MAPR). 2022 International Conference on Multimedia Analysis and Pattern Recognition (MAPR).; 2022. Available at: https://ieeexplore.ieee.org/abstract/document/9924821.
  6. COVID-Net Network and Application on Support Diagnosis COVID-19 over X-ray Images. In: 2022 International Conference on Multimedia Analysis and Pattern Recognition (MAPR). 2022 International Conference on Multimedia Analysis and Pattern Recognition (MAPR).; 2022. Available at: https://ieeexplore.ieee.org/abstract/document/9924841.
  7. Generating Vietnamese Language Caption Automatically for Scene Images. In: 2020 International Conference on Multimedia Analysis and Pattern Recognition (MAPR). 2020 International Conference on Multimedia Analysis and Pattern Recognition (MAPR).; 2020. Available at: https://ieeexplore.ieee.org/abstract/document/9237773.
  8. Extracting Handwritten Regions In Japanese Document Images. In: 2020 International Conference on Multimedia Analysis and Pattern Recognition (MAPR). 2020 International Conference on Multimedia Analysis and Pattern Recognition (MAPR).; 2020. Available at: https://ieeexplore.ieee.org/abstract/document/9237784.
  9. Image Captioning in Vietnamese Language Based on Deep Learning Network. In: Advances in Computational Collective Intelligence: 12th International Conference, ICCCI 2020. Advances in Computational Collective Intelligence: 12th International Conference, ICCCI 2020.; 2020. Available at: https://link.springer.com/chapter/10.1007/978-3-030-63119-2_64.