Search Results - "convolutional autoencoder"

Non-intrusive reduced order modeling of natural convection in porous media using convolutional autoencoders: Comparison with linear subspace techniques by Kadeethum, T., Ballarin, F., Choi, Y., O’Malley, D., Yoon, H., Bouklas, N.

“…Natural convection in porous media is a highly nonlinear multiphysical problem relevant to many engineering applications (e.g., the process of CO2…”
Get full text

A graph convolutional autoencoder approach to model order reduction for parametrized PDEs by Pichi, Federico, Moya, Beatriz, Hesthaven, Jan S.

“…The present work proposes a framework for nonlinear model order reduction based on a Graph Convolutional Autoencoder (GCA-ROM). In the reduced order modeling…”
Get full text

Surface defect classification of steels with a new semi-supervised learning method by Di, He, Ke, Xu, Peng, Zhou, Dongdong, Zhou

“…•A semi-supervised learning method named CAE-SGAN is proposed to classify surface defects of steels.•CAE-SGAN improves the performance of SGAN with limited…”
Get full text

Anomaly detection of defects on concrete structures with the convolutional autoencoder by Chow, J.K., Su, Z., Wu, J., Tan, P.S., Mao, X., Wang, Y.H.

“…•Deep learning model is applied for the anomaly detection of concrete defects.•The model training is in the unsupervised mode, with no label needed.•This…”
Get full text

From Clutter to Clarity: Enhancing Radar-Based Human Activity Recognition with Deep Attention and Feature Denoising by Wang, Huaijun, Li, Shuang, Bai, Bingqian, Li, Junhuai, Fei, Rong, Huang, Tao

“…Millimeter-wave radar offers advantages such as insensitivity to lighting conditions, strong environmental adaptability, non-contact sensing, and inherent…”
Get full text

Vessel Trajectory Anomaly Detection Based on Multi-scale Convolutional Autoencoder by Qi, Yuhao, Yang, Jiaxuan, Xu, Dongsheng, Shao, Ran, Duan, Yangyang, Wang, Yangjie

“…Traditional methods for detecting anomalies in vessel trajectories do not adequately account for the multidimensional characteristics of vessel behavior, and…”
Get full text

Hybrid robust convolutional autoencoder for unsupervised anomaly detection of machine tools under noises by Yan, Shen, Shao, Haidong, Xiao, Yiming, Liu, Bin, Wan, Jiafu

“…•A new FDD loss function to suppress the noises is designed.•Construct the PCDF module to enhance the robustness of the network.•The unsupervised anomaly…”
Get full text

Rearranged soft-introspective orthogonality regularized convolutional autoencoder for fault detection of multivariate processes by Wang, Chenmao, Lu, Zhiqiang, Yu, Jianbo

“…Modern industrial processes are developing towards scale and complexity, which poses high requirements for process monitoring. Autoencoder (AE) has gained…”
Get full text

Convolutional Autoencoder-Based Multispectral Image Fusion by Azarang, Arian, Manoochehri, Hafez E., Kehtarnavaz, Nasser

“…This paper presents a deep learning-based pansharpening method for fusion of panchromatic and multispectral images in remote sensing applications. This method…”
Get full text

MR‐DCAE: Manifold regularization‐based deep convolutional autoencoder for unauthorized broadcasting identification by Zheng, Qinghe, Zhao, Penghui, Zhang, Deliang, Wang, Hongjun

“…Nowadays, radio broadcasting plays an important role in people's daily life. However, unauthorized broadcasting stations may seriously interfere with normal…”
Get full text

Auto-AD: Autonomous Hyperspectral Anomaly Detection Network Based on Fully Convolutional Autoencoder by Wang, Shaoyu, Wang, Xinyu, Zhang, Liangpei, Zhong, Yanfei

“…Hyperspectral anomaly detection is aimed at detecting observations that differ from their surroundings, and is an active area of research in hyperspectral…”
Get full text

State of health estimation of lithium-ion battery with automatic feature extraction and self-attention learning mechanism by Jiang, Yiyue, Chen, Yuan, Yang, Fangfang, Peng, Weiwen

“…Accurate state of health (SOH) estimation is significantly important to ensure the safe and reliable operation of lithium-ion battery. Most existing…”
Get full text

Wind turbine fault diagnosis based on transfer learning and convolutional autoencoder with small-scale data by Li, Yanting, Jiang, Wenbo, Zhang, Guangyao, Shu, Lianjie

“…Condition monitoring and fault diagnosis for wind turbines can effectively reduce the impact of failures. However, many wind turbines cannot establish fault…”
Get full text

Commonality Autoencoder: Learning Common Features for Change Detection From Heterogeneous Images by Wu, Yue, Li, Jiaheng, Yuan, Yongzhe, Qin, A. K., Miao, Qi-Guang, Gong, Mao-Guo

“…Change detection based on heterogeneous images, such as optical images and synthetic aperture radar images, is a challenging problem because of their huge…”
Get full text

CNN and Convolutional Autoencoder (CAE) based real-time sensor fault detection, localization, and correction by Jana, Debasish, Patil, Jayant, Herkal, Sudheendra, Nagarajaiah, Satish, Duenas-Osorio, Leonardo

“…Increasing advances in sensing technologies and analytics have led to the proliferation of sensors to monitor structural and infrastructural systems. Accurate…”
Get full text

Unsupervised Deep Anomaly Detection for Multi-Sensor Time-Series Signals by Zhang, Yuxin, Chen, Yiqiang, Wang, Jindong, Pan, Zhiwen

“…Nowadays, multi-sensor technologies are applied in many fields, e.g., Health Care (HC), Human Activity Recognition (HAR), and Industrial Control System (ICS)…”
Get full text

Unsupervised VSP up- and downgoing wavefield separation via dual convolutional autoencoders by Lu, Cai, Mu, Zuochen, Zong, Jingjing, Wang, Tengyu

“…Vertical seismic profiling (VSP) is widely applied in the field of seismic exploration to deliver high-quality subsurface images and enable quantitative…”
Get full text

Finding Ground-based Radars in SAR images: Localizing Radio Frequency Interference using Unsupervised Deep Learning by Sorensen, Kristian Aa, Kusk, Anders, Heiselberg, Peder, Heiselberg, Henning

“…Synthetic Aperture Radar (SAR) satellite images are used increasingly more for Earth observation. While SAR images are useable in most conditions, they…”
Get full text

From data to dynamics: Reconstructing soliton collision phenomena in optical fibers using a convolutional autoencoder by Xu, Qibo, Rong, Jifang, Zeng, Qilin, Yuan, Xiaofang, Huang, Longnv, Yang, Hua

“…In this study, a convolutional autoencoder is constructed to extract and reconstruct the dynamical processes of soliton collisions in optical fibers. The model…”
Get full text

Convolutional Graph Thermography for Subsurface Defect Detection in Polymer Composites by Liu, Kaixin, Yu, Qing, Liu, Yi, Yang, Jianguo, Yao, Yuan

“…Infrared thermography for quality assessment of polymer composites has gained increasing attention with the development of various thermographic data analysis…”
Get full text