Deep learning-based super-resolution images for synchronous measurement of temperature and deformation at elevated temperature
Authors:
- Yunlong TangYTYunlong Tang
- Jinsong ZhangJZJinsong Zhang
- Mengkun YueMYMengkun Yue
- Zhe QuZQZhe Qu
- Xian WangXWXian Wang
- Yewei GuiYGYewei Gui
- Xue FengXFXue Feng
Abstract
No abstract availableKeywords
Funding Information
- National Natural Science Foundation of China (11320101001, 11625207, 11972326)
This publication has 26 references indexed in Scilit:
- Recent advances in convolutional neural networksPattern Recognition, 2018
- Formation mechanisms of characteristic structures on the surface of C/SiC composites subjected to thermal ablationJournal of the European Ceramic Society, 2016
- Measurements for displacement and deformation at high temperature by using edge detection of digital imageApplied Optics, 2015
- Image Super-Resolution Using Deep Convolutional NetworksIEEE Transactions on Pattern Analysis and Machine Intelligence, 2015
- Single-image superresolution based on local regression and nonlocal self-similarityJournal of Electronic Imaging, 2014
- Fast, Robust and Accurate Digital Image Correlation Calculation Without Redundant ComputationsExperimental Mechanics, 2013
- Morphological segmentation based on edge detection for sewer pipe defects on CCTV imagesExpert Systems with Applications, 2011
- Recent Progress in Digital Image CorrelationExperimental Mechanics, 2010
- Equivalence of digital image correlation criteria for pattern matchingApplied Optics, 2010
- Super-Resolution of Remotely Sensed Images With Variable-Pixel Linear ReconstructionIEEE Transactions on Geoscience and Remote Sensing, 2007