Li, XiaofengLiu, HaiZhou, FengChen, ZhongchangGiannakis, IraklisSlob, Evert2022-11-262022-11-262022-11-15Li, X, Liu, H, Zhou, F, Chen, Z, Giannakis, I & Slob, E 2022, 'Deep learning–based nondestructive evaluation of reinforcement bars using ground-penetrating radar and electromagnetic induction data', Computer-Aided Civil and Infrastructure Engineering, vol. 37, no. 14, pp. 1834-1853. https://doi.org/10.1111/mice.127981093-9687ORCID: /0000-0002-7672-8992/work/147566860https://hdl.handle.net/2164/19620Funding Information: The research was funded by the National Natural Science Foundation of China (41974165, 42111530126) and Hubei Key Laboratory of Intelligent Geo‐Information Processing (KLIGIP‐2018A2). The authors thank Zhiwei Duan and Xuefeng Yin for their contributions in the initial stage of the work, and the editor and anonymous reviewers for their constructive comments and suggestions to improve the quality of the paper.207697336engTA Engineering (General). Civil engineering (General)Civil and Structural EngineeringComputer Science ApplicationsComputer Graphics and Computer-Aided DesignComputational Theory and MathematicsTAJournal article10.1111/mice.12798http://www.scopus.com/inward/record.url?scp=85119989361&partnerID=8YFLogxK3714