Bin Dong

  • 1220 Citations
  • 16 h-Index
20062019
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Fingerprint Dive into the research topics where Bin Dong is active. These topic labels come from the works of this person. Together they form a unique fingerprint.

Wavelet Frames Mathematics
Image reconstruction Engineering & Materials Science
Image Restoration Mathematics
Tight Frame Mathematics
Level Set Mathematics
Partial differential equations Engineering & Materials Science
Denoising Mathematics
Tomography Engineering & Materials Science

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Research Output 2006 2019

Dynamically unfolding recurrent restorer: A moving endpoint control method for image restoration

Zhang, X., Liu, J., Lu, Y. & Dong, B., Jan 1 2019.

Research output: Contribution to conferencePaper

Image reconstruction
restoration
Degradation
Image denoising
Restoration

JSR-Net: A Deep Network for Joint Spatial-radon Domain CT Reconstruction from Incomplete Data

Zhang, H., Dong, B. & Liu, B., May 1 2019, 2019 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019 - Proceedings. Institute of Electrical and Electronics Engineers Inc., p. 3657-3661 5 p. 8682178. (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings; vol. 2019-May).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Radon
Medical imaging
Image reconstruction
Neural networks
Experiments
1 Citation (Scopus)

Multi-channel framelet denoising of diffusion-weighted images

Chen, G., Zhang, J., Zhang, Y., Dong, B., Shen, D. & Yap, P. T., Feb 1 2019, In : PLoS One. 14, 2, e0211621.

Research output: Contribution to journalArticle

Stairs
Water Movements
Diffusion Magnetic Resonance Imaging
Signal-To-Noise Ratio
Noise abatement

Nostalgic ADAM: Weighting more of the past gradients when designing the adaptive learning rate

Huang, H., Wang, C. & Dong, B., Jan 1 2019, Proceedings of the 28th International Joint Conference on Artificial Intelligence, IJCAI 2019. Kraus, S. (ed.). International Joint Conferences on Artificial Intelligence, p. 2556-2562 7 p. (IJCAI International Joint Conference on Artificial Intelligence; vol. 2019-August).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Data storage equipment
Experiments
Deep learning
1 Citation (Scopus)

PDE-Net 2.0: Learning PDEs from data with a numeric-symbolic hybrid deep network

Long, Z., Lu, Y. & Dong, B., Dec 15 2019, In : Journal of Computational Physics. 399, 108925.

Research output: Contribution to journalArticle

Numerics
partial differential equations
learning
Partial differential equations
Partial differential equation