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Results: 37
Number of items: 37
  • Open Access
    Najdenkoska, I., Zhen, X., Worring, M., & Shao, L. (2022). Uncertainty-aware report generation for chest X-rays by variational topic inference. Medical Image Analysis, 82, Article 102603. https://doi.org/10.1016/j.media.2022.102603
  • Najdenkoska, I., Zhen, X., Worring, M., & Shao, L. (2021). Variational Topic Inference for Chest X-Ray Report Generation. In M. de Bruijne, P. C. Cattin, S. Cotin, N. Padoy, S. Speidel, Y. Zheng, & C. Essert (Eds.), Medical Image Computing and Computer Assisted Intervention – MICCAI 2021: 24th International Conference, Strasbourg, France, September 27–October 1, 2021 : proceedings (Vol. III, pp. 625-635). (Lecture Notes in Computer Science; Vol. 12903). Springer. https://doi.org/10.1007/978-3-030-87199-4_59
  • van Sonsbeek, T., Zhen, X., Worring, M., & Shao, L. (2021). Variational Knowledge Distillation for Disease Classification in Chest X-Rays. In A. Feragen, S. Sommer, J. Schnabel, & M. Nielsen (Eds.), Information Processing in Medical Imaging: 27th International Conference, IPMI 2021, virtual event, June 28–June 30, 2021 : proceedings (pp. 334-345). (Lecture Notes in Computer Science; Vol. 12729). Springer. https://doi.org/10.1007/978-3-030-78191-0_26
  • Zhang, L., Zuo, L., Du, Y., & Zhen, X. (2021). Learning to Adapt with Memory for Probabilistic Few-Shot Learning. IEEE transactions on circuits and systems for video technology, 31(11), 4283-4292. https://doi.org/10.1109/TCSVT.2021.3052785
  • Xu, J., Liu, Z.-A., Hou, Y.-K., Zhen, X.-T., Shao, L., & Cheng, M.-M. (2021). Pixel-level Non-local Image Smoothing with Objective Evaluation. IEEE Transactions on Multimedia, 23, 4065-4078. https://doi.org/10.1109/TMM.2020.3037535
  • Open Access
    Qin, Z., Lu, X., Nie, X., Zhen, X., & Yin, Y. (2021). Learning Hierarchical Embedding for Video Instance Segmentation. In MM '21: Proceedings of the 29th ACM International Conference on Multimedia : October 20-24, 2021, Virtual Event, China (pp. 1884-1892). Association for Computing Machinery. https://doi.org/10.1145/3474085.3475342
  • Open Access
    Chen, H., Wang, J., Chen, H. C., Zhen, X., Zheng, F., Ji, R., & Shao, L. (2021). Seminar Learning for Click-Level Weakly Supervised Semantic Segmentation. In 2021 IEEE/CVF International Conference on Computer Vision: proceedings : ICCV 2021 : 11-17 October 2021, virtual event (pp. 6900-6909). (International Conference on Computer Vision; Vol. 18). IEEE Computer Society. https://doi.org/10.1109/ICCV48922.2021.00684
  • Open Access
    Zhen, X., Du, Y., Xiong, H., Qiu, Q., Snoek, C., & Shao, L. (2021). Learning to Learn Variational Semantic Memory. In H. Larochelle, M. Ranzato, R. Hadsell, M. F. Balcan, & H. Lin (Eds.), 34th Concerence on Neural Information Processing Systems (NeurIPS 2020): online, 6-12 December 2020 (Vol. 11, pp. 9122-9134). (Advances in Neural Information Processing Systems; Vol. 33). Neural Information Processing Systems Foundation. https://papers.nips.cc/paper/2020/hash/67d16d00201083a2b118dd5128dd6f59-Abstract.html
  • Open Access
    Xiao, Z., Shen, J., Zhen, X., Shao, L., & Snoek, C. G. M. (2021). A Bit More Bayesian: Domain-Invariant Learning with Uncertainty. Proceedings of Machine Learning Research, 139, 11351-11361. https://proceedings.mlr.press/v139/xiao21a.html
  • Open Access
    Wang, J., Tan, S., Zhen, X., Xu, S., Zheng, F., He, Z., & Shao, L. (2021). Deep 3D human pose estimation: A review. Computer Vision and Image Understanding, 210, Article 103225. https://doi.org/10.1016/j.cviu.2021.103225
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