Dung Doan

Dung Doan

HDR Student

School of Computer Science

Faculty of Engineering, Computer and Mathematical Sciences

My research interest is robotic vision, at the intersection of robotics, computer vision, and machine learning. After 6+ years of research experience, I acquired an extensive expertise in developing scalable algorithms for life-long visual localization & mapping, and large-scale image retrieval. My research enables applications such as self-driving cars, autonomous robots, and augmented reality.

My personal homepage: https://sites.google.com/view/dzungdoan/

  • Journals

    Year Citation
    2021 Doan, A. D., Latif, Y., Chin, T. J., Liu, Y., Ch’ng, S. F., Do, T. T., & Reid, I. (2021). Visual localization under appearance change: filtering approaches. Neural Computing and Applications, 33(13), 7325-7338.
    DOI WoS1
    2021 Doan, A. -D., Latif, Y., Chin, T. -J., & Reid, I. (2021). HM⁴: hidden Markov model with memory management for visual place recognition. IEEE Robotics and Automation Letters, 6(1), 167-174.
    2020 Do, T. T., Hoang, T., Le Tan, D. K., Doan, A. D., & Cheung, N. M. (2020). Compact Hash Code Learning with Binary Deep Neural Network. IEEE Transactions on Multimedia, 22(4), 992-1004.
    DOI Scopus6 WoS4
    2019 Ngoc-Trung, T., Dang-Khoa, L. T., Anh-Dzung, D., Thanh-Toan, D., Tuan-Anh, B., Tan, M., & Cheung, N. -M. (2019). On-Device Scalable Image-Based Localization via Prioritized Cascade Search and Fast One-Many RANSAC. IEEE TRANSACTIONS ON IMAGE PROCESSING, 28(4), 1675-1690.
    DOI WoS15 Europe PMC1
    Doan, A. -D., Jawaid, A. M., Do, T. -T., & Chin, T. -J. (n.d.). G2D: from GTA to Data.
  • Conference Papers

    Year Citation
    2020 Latif, Y., Doan, A., Chin, T., & Reid, I. (2020). SPRINT: Subgraph Place Recognition for INtelligent Transportation. In Proceedings of the 2020 IEEE International Conference on Robotics and Automation (pp. 5408-5414). online: IEEE.
    DOI Scopus2
    2019 Ch'ng, S. F., Khosravian Hemami, A., Doan, A., & Chin, T. J. (2019). Outlier-robust manifold pre-integration for INS/GPS fusion. In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2019) (pp. 7489-7496). online: IEEE.
    2019 Doan, D., Latif, Y., Chin, T., Liu, Y., Do, T., & Reid, I. (2019). Scalable place recognition under appearance change for autonomous driving. In Proceedings of the IEEE International Conference on Computer Vision Vol. 2019-October (pp. 9318-9327). online: IEEE.
    DOI Scopus12 WoS6
    2016 Thanh-Toan, D., Anh-Dzung, D., & Cheung, N. -M. (2016). Learning to Hash with Binary Deep Neural Network. In B. Leibe, J. Matas, N. Sebe, & M. Welling (Eds.), Unknown Conference Vol. 9909 (pp. 219-234). SPRINGER INTERNATIONAL PUBLISHING AG.
    DOI WoS74
    2016 Do, T. -T., Doan, D., Nguyen, D. -T., & Cheung, N. -M. (2016). Binary Hashing with Semidefinite Relaxation and Augmented Lagrangian. In European Conference on Computer Vision. Amsterdam, The Netherlands.
    2013 Doan, D. A., Ngoc-Trung, T., Dinh-Phong, V., Bac, L., & Yoshitaka, A. (2013). Combining Descriptors Extracted from Feature Maps of Deconvolutional Networks and SIFT Descriptors in Scene Image Classification. In B. Murgante, S. Misra, M. Carlini, C. M. Torre, H. Q. Nguyen, D. Taniar, . . . O. Gervasi (Eds.), COMPUTATIONAL SCIENCE AND ITS APPLICATIONS - ICCSA 2013, PT V Vol. 7975 (pp. 321-331). Ho Chi Minh City, VIETNAM: SPRINGER-VERLAG BERLIN.
    2013 Doan, D. A., Ngoc-Trung Tran., Dinh-Phong Vo., & Bac Le. (2013). Learned and designed features for sparse coding in image classification. In The 2013 RIVF International Conference on Computing & Communication Technologies - Research, Innovation, and Vision for Future (RIVF). IEEE.

Project supervisor

  • Master of Machine Learning Project
  • Master of Computing and Innovation Project

Teaching assistant

  • Foundation of Computer Science
  • Foundation of Computer Science (Python)
  • Programming MATLAB & C.
  • Position: HDR Student
  • Email: dung.doan@adelaide.edu.au
  • Campus: North Terrace
  • Building: Australian Institute for Machine Learning, floor 2
  • Room: 2.04.01
  • Org Unit: Australian Institute for Machine Learning

Connect With Me
External Profiles