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Changying "Charlie" Li
Changying "Charlie" Li
Professor of Agricultural & Biological Engineering, University of Florida; Adjunct Professor at UGA
Verified email at ufl.edu - Homepage
Title
Cited by
Cited by
Year
Sensing technologies for precision specialty crop production
WS Lee, V Alchanatis, C Yang, M Hirafuji, D Moshou, C Li
Computers and electronics in agriculture 74 (1), 2-33, 2010
6732010
Convolutional neural networks for image-based high-throughput plant phenotyping: a review
Y Jiang, C Li
Plant Phenomics, 2020
2292020
Neural network and Bayesian network fusion models to fuse electronic nose and surface acoustic wave sensor data for apple defect detection
C Li, P Heinemann, R Sherry
Sensors and Actuators B: Chemical 125 (1), 301-310, 2007
1512007
Measurement of optical properties of fruits and vegetables: A review
R Lu, R Van Beers, W Saeys, C Li, H Cen
Postharvest Biology and Technology 159, 111003, 2020
1482020
In-field high throughput phenotyping and cotton plant growth analysis using LiDAR
S Sun, C Li, AH Paterson, Y Jiang, R Xu, JS Robertson, JL Snider, ...
Frontiers in plant science 9, 16, 2018
1402018
Gas sensor array for blueberry fruit disease detection and classification
C Li, GW Krewer, P Ji, H Scherm, SJ Kays
Postharvest Biology and Technology 55 (3), 144-149, 2010
1332010
High throughput phenotyping of cotton plant height using depth images under field conditions
Y Jiang, C Li, AH Paterson
Computers and Electronics in Agriculture 130, 57-68, 2016
1272016
In-field high-throughput phenotyping of cotton plant height using LiDAR
S Sun, C Li, AH Paterson
Remote Sensing 9 (4), 377, 2017
1162017
Shortwave infrared hyperspectral imaging for detecting sour skin (Burkholderia cepacia)-infected onions
W Wang, C Li, EW Tollner, RD Gitaitis, GC Rains
Journal of Food Engineering 109 (1), 38-48, 2012
1032012
Aerial images and convolutional neural network for cotton bloom detection
R Xu, C Li, AH Paterson, Y Jiang, S Sun, JS Robertson
Frontiers in plant science 8, 2235, 2018
1002018
DeepSeedling: Deep convolutional network and Kalman filter for plant seedling detection and counting in the field
Y Jiang, C Li, AH Paterson, JS Robertson
Plant methods 15 (1), 141, 2019
922019
Three-dimensional photogrammetric mapping of cotton bolls in situ based on point cloud segmentation and clustering
S Sun, C Li, PW Chee, AH Paterson, Y Jiang, R Xu, JS Robertson, ...
ISPRS Journal of Photogrammetry and Remote Sensing 160, 195-207, 2020
892020
Detection of blueberry internal bruising over time using NIR hyperspectral reflectance imaging with optimum wavelengths
S Fan, C Li, W Huang, L Chen
Postharvest Biology and Technology 134, 55-66, 2017
892017
Multispectral imaging and unmanned aerial systems for cotton plant phenotyping
R Xu, C Li, AH Paterson
PloS one 14 (2), e0205083, 2019
882019
Simulation of an autonomous mobile robot for LiDAR-based in-field phenotyping and navigation
J Iqbal, R Xu, S Sun, C Li
Robotics 9 (2), 46, 2020
872020
Deep learning image segmentation and extraction of blueberry fruit traits associated with harvestability and yield
X Ni, C Li, H Jiang, F Takeda
Horticulture research 7, 2020
852020
Radio frequency heating of corn flour: Heating rate and uniformity
S Ozturk, F Kong, RK Singh, JD Kuzy, C Li
Innovative food science & emerging technologies 44, 191-201, 2017
842017
Detection of onion postharvest diseases by analyses of headspace volatiles using a gas sensor array and GC-MS
C Li, NE Schmidt, R Gitaitis
LWT-Food Science and Technology 44 (4), 1019-1025, 2011
822011
Size estimation of sweet onions using consumer-grade RGB-depth sensor
W Wang, C Li
Journal of food engineering 142, 153-162, 2014
792014
GPhenoVision: A ground mobile system with multi-modal imaging for field-based high throughput phenotyping of cotton
Y Jiang, C Li, JS Robertson, S Sun, R Xu, AH Paterson
Scientific reports 8 (1), 1213, 2018
782018
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