no code implementations • 22 Apr 2024 • Zhongqi Wang, Bingnan Wang, MaoSheng Xiang
We demonstrate that discrete PnP iteration can be described by a continuous stochastic differential equation (SDE).
no code implementations • 12 Apr 2023 • Shuang Cui, Bingnan Wang, Quan Zheng
To address the issues, we propose a novel aberration correction method with an invertible architecture by leveraging its information-lossless property.
no code implementations • 10 Feb 2023 • Bingnan Wang, Fanjiang Xu, Quan Zheng
The purpose of facial image deblurring is to recover a clear image from a blurry input image, which can improve the recognition accuracy, etc.
no code implementations • 25 Jul 2020 • Shen Zhang, Fei Ye, Bingnan Wang, Thomas G. Habetler
Most of the data-driven approaches applied to bearing fault diagnosis up-to-date are trained using a large amount of fault data collected a priori.
no code implementations • 2 Dec 2019 • Shen Zhang, Fei Ye, Bingnan Wang, Thomas G. Habetler
Most of the data-driven approaches applied to bearing fault diagnosis up to date are established in the supervised learning paradigm, which usually requires a large set of labeled data collected a priori.
no code implementations • 24 Jan 2019 • Shen Zhang, Shibo Zhang, Bingnan Wang, Thomas G. Habetler
In this paper, we first provide a brief review of conventional ML methods, before taking a deep dive into the state-of-the-art DL algorithms for bearing fault applications.