深度学习

深度学习是一种基于人工神经网络的信息处理方法，通过多层非线性变换自动学习数据特征，广泛应用于图像识别、自然语言处理和语音识别等领域，实现了高度的智能化和自动化，同时也面临着数据需求大、模型可解释性差等挑战。

论文

2025年

  1. Weiming Xiong, Mingyang Zhong, Shenglin Li, Haibin Zhu, Guojun Huang, Libo Zhang, RUL: Region Uncertainty Learning for Robust Face Recognition[J]. IEEE Transactions on Multimedia.(中科院一区)

2024年

  1. Dong Li, Weiming Xiong, Tao Luo, Libo Zhang*. 3WAUS: A novel three-way adaptive uncertainty-suppressing model for facial expression recognition[J]. Information Sciences, 2024, 677: 120962.(中科院二区)

2023年

  1. Mingyang Zhong, Weiming Xiong, Dong Li, Kehan Chen, Libo Zhang*. MaskDUF: Data uncertainty learning in masked face recognition with mask uncertainty fluctuation[J]. Expert Systems with Applications, 2024, 238: 121995.(中科院一区)

  2. Libo Zhang, Weiming Xiong, Ku Zhao, Kehan Chen, Mingyang Zhong. Maskdul: Data Uncertainty Learning in Masked Face Recognition[C]. In ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2023, pp. 1-5.(CCF B)

  3. Ku Zhao, Tao Luo, Kehan Chen, Libo Zhang*. Data Uncertainty Learning in Breast Cancer Recognition[C]. In 2023 5th International Conference on Data-driven Optimization of Complex Systems (DOCS), 2023, pp. 1-6.

2022年

  1. Weiming Xiong, Mingyang Zhong, Cong Guo, Huamin Wang, Libo Zhang*. MFGAN: A Novel CycleGAN-Based Network for Masked Face Generation[C]. In The Thirty Fourth International Conference on Software Engineering and Knowledge Engineering (SEKE 2022), 2022, pp. 112-117.(CCF C)