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.


My research interests lie in the area of robotic vision, at the intersection of robotics, computer vision, and machine learning.

Please visit my personal homepage (https://dzungdoan6.github.io/) for more information

  • Journals

    Year Citation
    2024 Doan, A. D., Nguyen, B. L., Gupta, S., Reid, I., Wagner, M., & Chin, T. J. (2024). Assessing domain gap for continual domain adaptation in object detection. Computer Vision and Image Understanding, 238, 10 pages.
    DOI
    2024 Nguyen, B. L., Doan, A. D., Chin, T. J., Guettier, C., Gupta, S., Parra, E., . . . Wagner, M. (2024). Sensor Allocation and Online-Learning-Based Path Planning for Maritime Situational Awareness Enhancement: A Multi-Agent Approach. IEEE Transactions on Intelligent Transportation Systems, 1-13.
    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 Scopus2 WoS2
    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 Scopus14 WoS12
    2020 Doan, A. D., Latif, Y., Chin, T. J., Liu, Y., Ch ng, S. F., Do, T. T., & Reid, I. (2020). Visual localization under appearance change: filtering approaches. Neural Computing and Applications, 33(13), 254-261.
    DOI Scopus2 WoS5
    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 Scopus27 WoS21 Europe PMC1
    2018 Doan, A. -D., Jawaid, A. M., Do, T. -T., & Chin, T. -J. (2018). G2D: from GTA to Data.
  • Conference Papers

    Year Citation
    2022 Sachdeva, R., Hammond, R., Bockman, J., Arthur, A., Smart, B., Craggs, D., . . . Reid, I. (2022). Autonomy and Perception for Space Mining. In 2022 International Conference on Robotics and Automation (ICRA) (pp. 4087-4093). Philadelphia, PA, USA: IEEE.
    DOI Scopus2
    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). Online: IEEE.
    DOI Scopus6 WoS1
    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 Scopus2 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 Scopus10 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 Scopus42 WoS29
    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 Scopus132 WoS126
    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. (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
    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
  • 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

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