Author of the publication

copy delete add this publication to your clipboard
community post
history of this post
URL
DOI
BibTeX
EndNote
APA
Chicago
DIN 1505
Harvard
MSOffice XML

Improved chlorophyll and water content estimations at leaf level with a hybrid radiative transfer and machine learning model.

J. Li, N. Wijewardane, Y. Ge, and Y. Shi. Comput. Electron. Agric., (March 2023)

Please choose a person to relate this publication to

To differ between persons with the same name, the academic degree and the title of an important publication will be displayed. You can also use the button next to the name to display some publications already assigned to the person.

Lei Shi

Huili Shi

Zhanjun Shi

Jian Shi

Renhu Shi

Other publications of authors with the same name

Improvement of a ground-LiDAR-based corn plant population and spacing measurement system.Y. Shi, N. Wang, R. Taylor, and W. Raun. Comput. Electron. Agric., (2015)Comparison of Object Detection and Patch-Based Classification Deep Learning Models on Mid- to Late-Season Weed Detection in UAV Imagery.A. Sivakumar, J. Li, S. Scott, E. Psota, A. Jhala, J. Luck, and Y. Shi. Remote. Sens., 12 (13): 2136 (2020)Maize Tassel Detection From UAV Imagery Using Deep Learning.A. Alzadjali, M. Alali, A. Sivakumar, J. Deogun, S. Scott, J. Schnable, and Y. Shi. Frontiers Robotics AI, (2021)UAVs for Vegetation Monitoring: Overview and Recent Scientific Contributions.A. de Castro, Y. Shi, J. Maja, and J. Peña. Remote. Sens., 13 (11): 2139 (2021)Registration for Optical Multimodal Remote Sensing Images Based on FAST Detection, Window Selection, and Histogram Specification.X. Zhao, J. Zhang, C. Yang, H. Song, Y. Shi, X. Zhou, D. Zhang, and G. Zhang. Remote. Sens., 10 (5): 663 (2018)Improving model robustness for soybean iron deficiency chlorosis rating by unsupervised pre-training on unmanned aircraft system derived images.J. Li, C. Oswald, G. Graef, and Y. Shi. Comput. Electron. Agric., (2020)GIS-based volunteer cotton habitat prediction and plant-level detection with UAV remote sensing.T. Wang, X. Mei, J. Thomasson, C. Yang, X. Han, P. Yadav, and Y. Shi. Comput. Electron. Agric., (2022)A lightweight SSV2-YOLO based model for detection of sugarcane aphids in unstructured natural environments.W. Xu, T. Xu, J. Thomasson, W. Chen, R. Karthikeyan, G. Tian, Y. Shi, C. Ji, and Q. Su. Comput. Electron. Agric., (August 2023)Vertical distribution and vortex structure of rotor wind field under the influence of rice canopy.J. Li, Y. Shi, Y. Lan, and S. Guo. Comput. Electron. Agric., (2019)Improved crop row detection with deep neural network for early-season maize stand count in UAV imagery.Y. Pang, Y. Shi, S. Gao, F. Jiang, A. Sivakumar, L. Thompson, J. Luck, and C. Liu. Comput. Electron. Agric., (2020)

BibSonomy

Disambiguation of "Shi, Yeyin"

copy delete add this publication to your clipboard
community post
history of this post
URL
DOI
BibTeX
EndNote
APA
Chicago
DIN 1505
Harvard
MSOffice XML

Improved chlorophyll and water content estimations at leaf level with a hybrid radiative transfer and machine learning model.

Please choose a person to relate this publication to

Lei Shi

Huili Shi

Zhanjun Shi

Jian Shi

Renhu Shi

Other publications of authors with the same name

Disambiguation

BibSonomy

Disambiguation of "Shi, Yeyin"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Improved chlorophyll and water content estimations at leaf level with a hybrid radiative transfer and machine learning model.

Please choose a person to relate this publication to

Lei Shi

Huili Shi

Zhanjun Shi

Jian Shi

Renhu Shi

Other publications of authors with the same name

Disambiguation

copy delete add this publication to your clipboard
community post
history of this post
URL
DOI
BibTeX
EndNote
APA
Chicago
DIN 1505
Harvard
MSOffice XML

Improved chlorophyll and water content estimations at leaf level with a hybrid radiative transfer and machine learning model.