Subject
- Agriculture 1
- Agronomy 1
- Botany 1
- Crop Science 1
- Plant Pathology 1
Creator
- Andres P. Cruz 2
- Brenden Lane 2
- Dong-Yeop Na 2
- Edward J. Delp 2
- Nathan M. Kleczewski 2
- Sriram Baireddy 2
- Adam Nicholas Brock 1
- Carlos Gongora 1
- Carlos Gongora-Canul 1
- Carlos Gongora-Canul, 0000-0003-2392-193X 1
Type
- Dataset 4
Date
subject: Botany and Plant Pathology type: dataset
Total is 4 Results
Contour-based detection and quantification of tar spot stromata using RGB images of maize leaves
10.4231/A5B3-XV27
Andres P. Cruz
,
Brenden Lane
,
Carlos Gongora-Canul
,
Christian D. Cruz
,
Da-Young Lee
,
Darcy E. P. Telenko
,
Dong-Yeop Na
,
Edward J. Delp
,
Nathan M. Kleczewski
,
Sriram Baireddy
06/30/2021
This dataset contains RGB images of the tar spot-infected corn leaves created for testing algorithm that uses contour analysis-based quantification of tar spot stromata.
Botany and Plant Pathology contour analysis image maize RGB imagery plant disease intensity RGB image dataset stromata detection and quantification
Contour-based detection and quantification of tar spot stromata using RGB images of maize leaves
10.4231/SCQM-M479
Andres P. Cruz
,
Brenden Lane
,
Carlos Gongora-Canul
,
Christian D. Cruz
,
Da-Young Lee
,
Darcy E. P. Telenko
,
Dong-Yeop Na
,
Edward J. Delp
,
Mariela Fernández-Campos
,
Nathan M. Kleczewski
,
Sriram Baireddy
,
Stephen Goodwin
08/10/2021
This dataset contains RGB images of the tar spot-infected corn leaves created for testing algorithm that uses contour analysis-based quantification of tar spot stromata.
Botany and Plant Pathology emerging epidemic plant disease phenotyping stromata detection and quantification tar spot of corn temporal analysis
Uniform Soybean Tests Northern Region 2020
10.4231/ZWFR-8Y15
Adam Nicholas Brock , Guohong Cai
05/09/2022
This dataset contains tables prepared for the 2020 Uniform Soybean Tests Northern Region Report.
Agriculture Agronomy Botany Botany and Plant Pathology Crop Science Plant Pathology Soybeans USDA-ARS
Wheat spike blast image classification using deep convolutional neural networks
10.4231/P0Y7-3428
Carlos Gongora
,
Christian D Cruz
,
Darcy Telenko
,
Jian Jin
,
Mariela Fernandez-Campos
,
Mohammad Jahanshahi
,
Tao Wang
,
Yuting Huang
04/30/2021
The folder includes i) a wheat spike blast image classification CNN model trained to automatically quantify and classify disease severity, ii) the generated datasets that include images of wheat spike blast severity levels under controlled...
Blast Botany and Plant Pathology CNN deep learning disease Magnaporthe oryzae plant disease phenotyping Plant phenotyping Python Wheat wheat blast
Display #
Results 1 - 4 of 4