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Cited by in F6Publishing
For: Traore A, Ata-ul-karim ST, Duan A, Soothar MK, Traore S, Zhao B. Predicting Equivalent Water Thickness in Wheat Using UAV Mounted Multispectral Sensor through Deep Learning Techniques. Remote Sensing 2021;13:4476. [DOI: 10.3390/rs13214476] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 2.0] [Reference Citation Analysis]
Number Citing Articles
1 Meiyan S, Qizhou D, Shuaipeng F, Xiaohong Y, Jinyu Z, Lei M, Baoguo L, Yuntao M. Improved estimation of canopy water status in maize using UAV-based digital and hyperspectral images. Computers and Electronics in Agriculture 2022;197:106982. [DOI: 10.1016/j.compag.2022.106982] [Reference Citation Analysis]