Wei Guo
Wei Guo
在 isas.a.u-tokyo.ac.jp 的电子邮件经过验证
标题引用次数年份
Illumination invariant segmentation of vegetation for time series wheat images based on decision tree model
W Guo, UK Rage, S Ninomiya
Computers and electronics in agriculture 96, 58-66, 2013
1312013
On plant detection of intact tomato fruits using image analysis and machine learning methods
K Yamamoto, W Guo, Y Yoshioka, S Ninomiya
Sensors 14 (7), 12191-12206, 2014
982014
High-throughput phenotyping of sorghum plant height using an unmanned aerial vehicle and its application to genomic prediction modeling
K Watanabe, W Guo, K Arai, H Takanashi, H Kajiya-Kanegae, ...
Frontiers in plant science 8, 421, 2017
872017
Comparison of ground cover estimates from experiment plots in cotton, sorghum and sugarcane based on images and ortho-mosaics captured by UAV
T Duan, B Zheng, W Guo, S Ninomiya, Y Guo, SC Chapman
Functional Plant Biology 44 (1), 169-183, 2017
582017
Automated characterization of flowering dynamics in rice using field-acquired time-series RGB images
W Guo, T Fukatsu, S Ninomiya
Plant methods 11 (1), 7, 2015
552015
EasyPCC: benchmark datasets and tools for high-throughput measurement of the plant canopy coverage ratio under field conditions
W Guo, B Zheng, T Duan, T Fukatsu, S Chapman, S Ninomiya
Sensors 17 (4), 798, 2017
192017
Aerial imagery analysis–quantifying appearance and number of sorghum heads for applications in breeding and agronomy
W Guo, B Zheng, AB Potgieter, J Diot, K Watanabe, K Noshita, DR Jordan, ...
Frontiers in plant science 9, 1544, 2018
142018
A Weakly Supervised Deep Learning Framework for Sorghum Head Detection and Counting
S Ghosal, B Zheng, SC Chapman, AB Potgieter, DR Jordan, X Wang, ...
Plant Phenomics 2019, 2019
102019
Node detection and internode length estimation of tomato seedlings based on image analysis and machine learning
K Yamamoto, W Guo, S Ninomiya
Sensors 16 (7), 1044, 2016
102016
A simple visible and near-infrared (V-NIR) camera system for monitoring the leaf area index and growth stage of Italian ryegrass
X Fan, K Kawamura, W Guo, TD Xuan, J Lim, N Yuba, Y Kurokawa, ...
Computers and electronics in agriculture 144, 314-323, 2018
92018
Characterization of peach tree crown by using high-resolution images from an unmanned aerial vehicle
Y Mu, Y Fujii, D Takata, B Zheng, K Noshita, K Honda, S Ninomiya, W Guo
Horticulture research 5 (1), 1-10, 2018
82018
McGET: A rapid image-based method to determine the morphological characteristics of gravels on the Gobi desert surface
Y Mu, F Wang, B Zheng, W Guo, Y Feng
Geomorphology 304, 89-98, 2018
82018
Pixel size of aerial imagery constrains the applications of unmanned aerial vehicle in crop breeding
P Hu, W Guo, SC Chapman, Y Guo, B Zheng
ISPRS Journal of Photogrammetry and Remote Sensing 154, 1-9, 2019
62019
Automatic detecting and counting of sorghum heads in breeding field using RGB imagery from UAV.
W Guo, AB Potgieter, D Jordan, R Armstrong, K Lawn, W Kakeru, T Duan, ...
CIGR-AgEng Conference, 26-29 June 2016, Aarhus, Denmark. Abstracts and Full …, 2016
32016
Visible, near infrared, and thermal spectral radiance on-board uavs for high-throughput phenotyping of plant breeding trials
SC Chapman, B Zheng, A Potgieter, W Guo, B Frederic, S Liu, S Madec, ...
Biophys. Biochem. Charact. Plant Species Stud 3, 275, 2018
22018
The Use of In-Situ Proximal Sensing Technologies to Determine Crop Characteristics in Sorghum Crop Breeding
AB Potgieter, DR Jordan, GL Hammer, RN Armstrong, G McLean, K Laws, ...
Tropical Agricultre Conference 2015, 2015
22015
Active Learning with Weak Supervision for Cost-Effective Panicle Detection in Cereal Crops
AC Lagandula, SV Desai, VN Balasubramanian, S Ninomiya, W Guo
arXiv preprint arXiv:1910.01789, 2019
12019
Automatic estimation of heading date of paddy rice using deep learning
SV Desai, VN Balasubramanian, T Fukatsu, S Ninomiya, W Guo
Plant Methods 15, 76, 2019
12019
Automatic estimation of heading date of paddy rice using deep learning
SV Desai, VN Balasubramanian, T Fukatsu, S Ninomiya, W Guo
arXiv preprint arXiv:1906.07917, 2019
12019
ゲノミックセレクションおよびハイスルプットフェノタイピングを用いた作物育種の効率化·高速化(Genomic selection and high-throughput phenotyping to increase the efficiency and speed of crop breeding)
W Guo, H Iwata
光合成研究 28 (3), 180-193, 2018
1*2018
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