Mr Hu Wang

Postdoc Research Fellow

Australian Institute for Machine Learning - Projects

Faculty of Sciences, Engineering and Technology

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


  • Journals

    Year Citation
    2024 Xie, Y., Zhang, J., Liu, L., Wang, H., Ye, Y., Johan, V., & Xia, Y. (2024). ReFs: A hybrid pre-training paradigm for 3D medical image segmentation. Medical Image Analysis, 91, 10 pages.
    DOI
    2023 Wang, Z., Byrnes, O., Wang, H., Sun, R., Ma, C., Chen, H., . . . Xue, M. (2023). Data Hiding With Deep Learning: A Survey Unifying Digital Watermarking and Steganography. IEEE Transactions on Computational Social Systems, 10(6), 2985-2999.
    DOI Scopus6
    2023 Ma, C., Zhang, W. E., Guo, M., Wang, H., & Sheng, Q. Z. (2023). Multi-document Summarization via Deep Learning Techniques: A Survey. ACM COMPUTING SURVEYS, 55(5), 37 pages.
    DOI Scopus34 WoS15
    2022 Lu, H., Liu, L., Wang, H., & Cao, Z. (2022). Counting Crowd by Weighing Counts: A Sequential Decision-Making Perspective. IEEE Transactions on Neural Networks and Learning Systems, 35(4), 14 pages.
    DOI WoS2
    2021 Wang, H., Chen, H., Wu, Q., Ma, C., & Li, Y. (2021). Multi-Intersection Traffic Optimisation: A Benchmark Dataset and a Strong Baseline. IEEE Open Journal of Intelligent Transportation Systems, 3, 126-136.
    DOI Scopus6 WoS2
  • Conference Papers

    Year Citation
    2024 Wu, R., Wang, H., Dayoub, F., & Chen, H. T. (2024). Segment beyond View: Handling Partially Missing Modality for Audio-Visual Semantic Segmentation. In Proceedings of the AAAI Conference on Artificial Intelligence Vol. 38 (pp. 6100-6108). Association for the Advancement of Artificial Intelligence (AAAI).
    DOI
    2023 Chen, Y., Liu, F., Wang, H., Wang, C., Liu, Y., Tian, Y., & Carneiro, G. (2023). BoMD: Bag of Multi-label Descriptors for Noisy Chest X-ray Classification. In Proceedings of the IEEE International Conference on Computer Vision (pp. 21227-21238). IEEE.
    DOI
    2023 Hull, M. L., Wang, H., Zhang, Y., Avery, J., To, M. S., Carneiro, G., & Butler, D. (2023). The Effectiveness of Self-supervised Pre-training for Multi-modal Endometriosis Classification.. In Proceedings of the 45th IEEE Engineering in Medicine and Biology Society Vol. 2023 (pp. 5 pages). Online: IEEE.
    DOI
    2023 Zhang, Y., Wang, H., Avery, J. C., & Hull, M. L. (2023). Distilling Missing Modality Knowledge from Ultrasound for Endometriosis Diagnosis with Magnetic Resonance Images. In 2023 IEEE 20th International Symposium on Biomedical Imaging (ISBI) Vol. 2023-April (pp. 1-5). Cartagena de Indias Colombia: IEEE.
    DOI Scopus1
    2023 Hu, P., Wang, Z., Sun, R., Wang, H., & Xue, M. (2023). M<sup>4</sup>I: Multi-modal Models Membership Inference. In Advances in Neural Information Processing Systems Vol. 35. USA: Neural information processing systems foundation.
    Scopus3
    2023 Wang, H., Ma, C., Zhang, J., Zhang, Y., Avery, J., Hull, L., & Carneiro, G. (2023). Learnable Cross-modal Knowledge Distillation for Multi-modal Learning with Missing Modality. In H. Greenspan, A. Madabhushi, P. Mousavi, S. Salcudean, J. Duncan, T. Syeda-Mahmood, & R. Taylor (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 14223 LNCS (pp. 216-226). CANADA, Vancouver: SPRINGER INTERNATIONAL PUBLISHING AG.
    DOI
    2022 Chen, Y., Wang, H., Wang, C., Tian, Y., Liu, F., Liu, Y., . . . Carneiro, G. (2022). Multi-view Local Co-occurrence and Global Consistency Learning Improve Mammogram Classification Generalisation. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 13433 LNCS (pp. 3-13). Online: Springer.
    DOI Scopus2 WoS1
    2022 Wang, H., Zhang, J., Chen, Y., Ma, C., Avery, J., Hull, L., & Carneiro, G. (2022). Uncertainty-Aware Multi-modal Learning via Cross-Modal Random Network Prediction. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 13697 LNCS (pp. 200-217). Online: Springer Nature Switzerland.
    DOI Scopus2
    2021 Wang, H., Chen, P., Zhuang, B., & Shen, C. (2021). Fully Quantized Image Super-Resolution Networks. In MM '21: Proceedings of the 29th ACM International Conference on Multimedia (pp. 639-647). New York, USA: ACM.
    DOI Scopus12 WoS7
    2021 Chen, L., Wang, H., Zhao, B. Z. H., Xue, M., & Qian, H. (2021). Oriole: Thwarting Privacy Against Trustworthy Deep Learning Models. In Proceedings of the 26th Australasian Conference, (ACISP 2021), as published in Lecture Notes in Computer Science Vol. 13083 (pp. 550-568). Switzerland: Springer International Publishing.
    DOI Scopus1
    2020 Wang, H., Wu, Q., & Shen, C. (2020). Soft Expert Reward Learning for Vision-and-Language Navigation. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 12354 LNCS (pp. 126-141). Switzerland: Springer Nature.
    DOI Scopus19
    2020 Wang, H., Pang, G., Shen, C., & Ma, C. (2020). Unsupervised representation learning by predicting random distances. In IJCAI International Joint Conference on Artificial Intelligence Vol. 2021-January (pp. 2950-2956). online: AAAI Press.
    Scopus24 WoS9
    2019 Ma, C., Wang, H., & Hoi, S. C. H. (2019). Multi-label Thoracic Disease Image Classification with Cross-Attention Networks. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 11769 LNCS (pp. 730-738). Switzerland: Springer International.
    DOI Scopus31 WoS21
  • Position: Postdoc Research Fellow
  • Email: hu.wang@adelaide.edu.au
  • Campus: Lot 14
  • Building: Australian Institute for Machine Learning Building, floor Second Floor
  • Org Unit: Australian Institute for Machine Learning - Operations

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