Dzung Doan

Dzung Doan

Grant Funded Researcher A

School of Computer Science

Faculty of Sciences, Engineering and Technology

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:

  • 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 Scopus1 WoS2
    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, D., & Cheung, N. M. (2020). Compact Hash Code Learning with Binary Deep Neural Network. IEEE Transactions on Multimedia, 22(4), 992-1004.
    DOI Scopus8 WoS9
    2019 Tran, N. -T., Le Tan, D. -K., Doan, A. -D., Do, T. -T., Bui, T. -A., 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 Scopus24 WoS18 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
    2021 Doan, D., Turmukhambetov, D., Latif, Y., Chin, T. J., & Bae, S. (2021). Learning to Predict Repeatability of Interest Points. In Proceedings - IEEE International Conference on Robotics and Automation Vol. 2021-May (pp. 10294-10301). online: IEEE.
    2020 Latif, Y., Doan, A. D., Chin, T. J., & 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 Scopus3 WoS3
    2019 Doan, A. -D., Latif, Y., Chin, T., Liu, Y., Ch'ng, S., Do, T. -T., & Reid, I. D. (2019). Visual Localization under Appearance Change: A Filtering Approach.. In Proceedings of 2019 Digital Image Computing Techniques and Applications (DICTA) (pp. 254-261). online: IEEE.
    DOI Scopus3
    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.
    DOI Scopus5 WoS3
    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 Scopus22 WoS12
    2016 Do, T. -T., Doan, A. -D., & Cheung, N. -M. (2016). Learning to Hash with Binary Deep Neural Network. In Lecture Notes in Computer Science Vol. 9909 LNCS (pp. 219-234). Amsterdam, The Netherlands: Springer International Publishing.
    DOI Scopus106 WoS102
    2016 Do, T. -T., Doan, D., Nguyen, D. -T., & Cheung, N. -M. (2016). Binary Hashing with Semidefinite Relaxation and Augmented Lagrangian. In Computer Vision – ECCV 2016 14th European Conference, Amsterdam, The Netherlands, October 11-14, 2016, Proceedings, Part II (pp. 802-817). Switzerland: Springer.
    2013 Doan, D. A., Tran, N. T., Vo, D. P., Le, B., & 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.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 7971 (pp. 321-331). Ho Chi Minh City, VIETNAM: SPRINGER-VERLAG BERLIN.
    2013 Doan, D. A., Tran, N. T., Vo, D. P., & Le, B. (2013). Learned and designed features for sparse coding in image classification. In Proceedings - 2013 RIVF International Conference on Computing and Communication Technologies: Research, Innovation, and Vision for Future, RIVF 2013 (pp. 237-241). 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: Grant Funded Researcher A
  • Email:
  • Campus: North Terrace
  • Building: Australian Institute for Machine Learning, floor 2
  • Org Unit: School of Computer Science

Connect With Me
External Profiles