Yeyin Shi
Yeyin Shi
Associate Professor and Agricultural Intelligence Engineer at University of Nebraska-Lincoln
Verifisert e-postadresse på unl.edu - Startside
Sitert av
Sitert av
Unmanned aerial vehicles for high-throughput phenotyping and agronomic research
Y Shi, JA Thomasson, SC Murray, NA Pugh, WL Rooney, S Shafian, ...
PloS one 11 (7), e0159781, 2016
Comparison of object detection and patch-based classification deep learning models on mid-to late-season weed detection in UAV imagery
AN Veeranampalayam Sivakumar, J Li, S Scott, E Psota, A J. Jhala, ...
Remote Sensing 12 (13), 2136, 2020
Unmanned aerial systems-based remote sensing for monitoring sorghum growth and development
S Shafian, N Rajan, R Schnell, M Bagavathiannan, J Valasek, Y Shi, ...
PloS one 13 (5), e0196605, 2018
Detection of multi-tomato leaf diseases (late blight, target and bacterial spots) in different stages by using a spectral-based sensor
J Lu, R Ehsani, Y Shi, AI de Castro, S Wang
Scientific reports 8 (1), 2793, 2018
Wheat height estimation using LiDAR in comparison to ultrasonic sensor and UAS
W Yuan, J Li, M Bhatta, Y Shi, PS Baenziger, Y Ge
Sensors 18 (11), 3731, 2018
Elucidating sorghum biomass, nitrogen and chlorophyll contents with spectral and morphological traits derived from unmanned aircraft system
J Li, Y Shi, AN Veeranampalayam-Sivakumar, DP Schachtman
Frontiers in plant science 9, 398877, 2018
Ag-IoT for crop and environment monitoring: Past, present, and future
N Chamara, MD Islam, GF Bai, Y Shi, Y Ge
Agricultural systems 203, 103497, 2022
UAVs for vegetation monitoring: Overview and recent scientific contributions
AI de Castro, Y Shi, JM Maja, JM Peña
Remote Sensing 13 (11), 2139, 2021
Field detection of anthracnose crown rot in strawberry using spectroscopy technology
J Lu, R Ehsani, Y Shi, J Abdulridha, AI de Castro, Y Xu
computers and electronics in agriculture 135, 289-299, 2017
Rapeseed seedling stand counting and seeding performance evaluation at two early growth stages based on unmanned aerial vehicle imagery
B Zhao, J Zhang, C Yang, G Zhou, Y Ding, Y Shi, D Zhang, J Xie, Q Liao
Frontiers in Plant Science 9, 1362, 2018
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, AN Veeranampalayam-Sivakumar, ...
Computers and Electronics in Agriculture 178, 105766, 2020
Distribution characteristics on droplet deposition of wind field vortex formed by multi-rotor UAV
S Guo, J Li, W Yao, Y Zhan, Y Li, Y Shi
PloS one 14 (7), e0220024, 2019
Damage mapping of powdery mildew in winter wheat with high-resolution satellite image
L Yuan, J Zhang, Y Shi, C Nie, L Wei, J Wang
Remote sensing 6 (5), 3611-3623, 2014
Research progress on airflow characteristics and field pesticide application system of rotary-wing UAV.
J Li, YB Lan, YY Shi
Transactions of the Chinese Society of Agricultural Engineering 34 (12), 104-118, 2018
Vertical distribution and vortex structure of rotor wind field under the influence of rice canopy
J Li, Y Shi, Y Lan, S Guo
Computers and Electronics in Agriculture 159, 140-146, 2019
Improvement of a ground-LiDAR-based corn plant population and spacing measurement system
Y Shi, N Wang, RK Taylor, WR Raun
Computers and Electronics in Agriculture 112, 92-101, 2015
Principal variable selection to explain grain yield variation in winter wheat from features extracted from UAV imagery
J Li, AN Veeranampalayam-Sivakumar, M Bhatta, ND Garst, H Stoll, ...
Plant Methods 15, 1-13, 2019
Mapping wheat rust based on high spatial resolution satellite imagery
D Chen, Y Shi, W Huang, J Zhang, K Wu
Computers and electronics in agriculture 152, 109-116, 2018
Automatic corn plant location and spacing measurement using laser line-scan technique
Y Shi, N Wang, RK Taylor, WR Raun, JA Hardin
Precision Agriculture 14, 478-494, 2013
Maize tassel detection from UAV imagery using deep learning
A Alzadjali, MH Alali, AN Veeranampalayam Sivakumar, JS Deogun, ...
Frontiers in Robotics and AI 8, 600410, 2021
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Artikler 1–20