{"title":"封面:利用领域分解法改进基于深度学习的数字图像相关性》,作者:Y. Chi、Y. Liu、B. Pan","authors":"","doi":"10.1007/s11340-024-01062-0","DOIUrl":null,"url":null,"abstract":"","PeriodicalId":552,"journal":{"name":"Experimental Mechanics","volume":"64 4","pages":"453 - 453"},"PeriodicalIF":2.0000,"publicationDate":"2024-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"On the Cover: Improving Deep Learning Based Digital Image Correlation with Domain Decomposition Method by Y. Chi, Y. Liu, B. Pan\",\"authors\":\"\",\"doi\":\"10.1007/s11340-024-01062-0\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\",\"PeriodicalId\":552,\"journal\":{\"name\":\"Experimental Mechanics\",\"volume\":\"64 4\",\"pages\":\"453 - 453\"},\"PeriodicalIF\":2.0000,\"publicationDate\":\"2024-03-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Experimental Mechanics\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://link.springer.com/article/10.1007/s11340-024-01062-0\",\"RegionNum\":3,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"MATERIALS SCIENCE, CHARACTERIZATION & TESTING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Experimental Mechanics","FirstCategoryId":"5","ListUrlMain":"https://link.springer.com/article/10.1007/s11340-024-01062-0","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATERIALS SCIENCE, CHARACTERIZATION & TESTING","Score":null,"Total":0}
期刊介绍:
Experimental Mechanics is the official journal of the Society for Experimental Mechanics that publishes papers in all areas of experimentation including its theoretical and computational analysis. The journal covers research in design and implementation of novel or improved experiments to characterize materials, structures and systems. Articles extending the frontiers of experimental mechanics at large and small scales are particularly welcome.
Coverage extends from research in solid and fluids mechanics to fields at the intersection of disciplines including physics, chemistry and biology. Development of new devices and technologies for metrology applications in a wide range of industrial sectors (e.g., manufacturing, high-performance materials, aerospace, information technology, medicine, energy and environmental technologies) is also covered.