Dzung Doan

Dzung Doan

Grant Funded Researcher A

School of Computer and Mathematical Sciences

Faculty of Sciences, Engineering and Technology

Eligible to supervise Masters and PhD (as Co-Supervisor) - email supervisor to discuss availability.

I am currently a postdoctoral researcher at Australian Institute for Machine Learning (AIML). I obtained my PhD degree at School of Computer Science, The University of Adelaide, under the guidance of Prof. Tat-Jun Chin, Dr. Yasir Latif, and Prof. Ian Reid. My research interest is robotic vision, at the intersection of robotics, computer vision, and machine learning.

I have published 10+ papers in major AI conferences & journal and 1 patent pending, won IEEE RA-L best paper award and APRS/IAPR Best Paper Award in DICTA 2019, regularly reviewed for major AI conferences & journal, and held research positions and collaborated with Safran (France), Niantic (USA), Australian Centre for Robotic Vision (Australia), Temasek Labs@SUTD (Singapore), Japan Advanced Institute of Science and Technology (Japan), and FIT@HCMUS (Vietnam).

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

  • Journals
    Year Citation
    2022 Sachdeva, R., Hammond, R., Bockman, J., Arthur, A., Smart, B., Craggs, D., . . . Reid, I. (2022). Autonomy and Perception for Space Mining. Proceedings - IEEE International Conference on Robotics and Automation, 4087-4093.
    DOI
    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.
    DOI Scopus1 WoS1
    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 WoS4
    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 Scopus10 WoS11
    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 Scopus26 WoS21 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
    2022 Doan, A. D., Sasdelli, M., Suter, D., & Chin, T. J. (2022). A Hybrid Quantum-Classical Algorithm for Robust Fitting. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2022) Vol. 2022-June (pp. 417-427). New Orleans, Louisiana: IEEE.
    DOI Scopus1
    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.
    DOI Scopus1 WoS1
    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 Scopus8 WoS7
    2019 Doan, D., Latif, Y., Chin, T. J., Liu, Y., Do, T. 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 Scopus29 WoS23
    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 Scopus113 WoS116
    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.
    DOI
    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.
    DOI
    2013 Doan, D. A., Tran, N. T., Vo, D. P., & Le, B. (2013). Learned and designed features for sparse coding in image classification. In N. T. Thuy, M. Ogawa, V. Piuri, X. T. Tran, & T. B. Ho (Eds.), Proceedings - 2013 RIVF International Conference on Computing and Communication Technologies: Research, Innovation, and Vision for Future, RIVF 2013 (pp. 237-241). Hanoi, VIETNAM: IEEE.
    DOI

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: dzung.doan@adelaide.edu.au
  • Campus: North Terrace
  • Building: Australian Institute for Machine Learning, floor 2
  • Org Unit: Computer Science
Connect With Me
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