no code implementations • 8 Apr 2024 • Xu Wu, Xianxu Hou, Zhihui Lai, Jie zhou, Ya-nan Zhang, Witold Pedrycz, Linlin Shen
Low-light image enhancement (LLIE) aims to improve low-illumination images.
no code implementations • 20 Dec 2023 • Lesego Moloko, Pavel Bokov, Xu Wu, Kostadin Ivanov
The aim of this work is to improve the ML models for the control assemblies by a combination of supervised and unsupervised ML algorithms.
no code implementations • 19 Aug 2023 • Farah Alsafadi, Xu Wu
Deep learning (DL) has achieved remarkable successes in many disciplines such as computer vision and natural language processing due to the availability of ``big data''.
no code implementations • 18 Aug 2023 • Mahmoud Yaseen, Dewen Yushu, Peter German, Xu Wu
The goal of this work is to develop an accurate and fast-running reduced order model (ROM) for this MOOSE-based AM model that can be used in a DRL-based process control and optimization method.
no code implementations • 4 Aug 2023 • Mahmoud Yaseen, Dewen Yushu, Peter German, Xu Wu
More specifically, we used the Fourier neural operator (FNO) and deep operator network (DeepONet) to develop ROMs for time-dependent responses.
no code implementations • 10 Jul 2023 • Ziyu Xie, Mahmoud Yaseen, Xu Wu
This work focuses on developing an inverse UQ process for time-dependent responses, using dimensionality reduction by functional principal component analysis (PCA) and deep neural network (DNN)-based surrogate models.
no code implementations • 1 Jul 2023 • Shuzhe Chen, Li Li, Zhichao Lin, Ke Zhang, Ying Gong, Lu Wang, Xu Wu, Maokun Li, Yuanlin Song, Fan Yang, Shenheng Xu
A simple convolutional neural network is used for classification.
no code implementations • 16 Nov 2022 • Lesego E. Moloko, Pavel M. Bokov, Xu Wu, Kostadin N. Ivanov
In this study, Deep Neural Networks (DNNs) are used to predict the assembly axial neutron flux profiles in the SAFARI-1 research reactor, with quantified uncertainties in the ANN predictions and extrapolation to cycles not used in the training process.
no code implementations • 27 Jun 2022 • Mahmoud Yaseen, Xu Wu
In this work, we focus on UQ of ML models as a preliminary step of ML VVUQ, more specifically, Deep Neural Networks (DNNs) because they are the most widely used supervised ML algorithm for both regression and classification tasks.
no code implementations • 4 Apr 2022 • Xin Zhao, Xu Wu, Lin Wang, Pengkun Hou, Qinfei Li, Yuxuan Zhang, Bo Yang
In experiments, the method is verified on actual 3D Micro-CT images and 2D BSE images.