Datasets

Creator
Type
Date

subject: Botany and Plant Pathology subject: plant disease phenotyping type: dataset

Total is 2 Results
Wheat spike blast image classification using deep convolutional neural networks

10.4231/P0Y7-3428

Carlos Gongora , Christian D Cruz ORCID logo , Darcy Telenko , Jian Jin , Mariela Fernandez-Campos ORCID logo , 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

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 ORCID logo , 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

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