Subject
Creator
- Byung-cheol Min, 0000-0001-6458-4365 1
- Carlos Gongora 1
- Christian D Cruz, 0000-0002-2287-6754 1
- Darcy Telenko 1
- Haozhe Zhou 1
- Jiacheng Zhang, 0000-0002-9027-6531 1
- Jian Jin 1
- Lalit Rajendran, 0000-0002-5673-6063 1
- Mariela Fernandez-Campos, 0000-0001-7736-9939 1
- Mohammad Jahanshahi 1
Type
- Dataset 3
Date
- 2021 3
Total is 3 Results
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
RoboMal Malware Detection Dataset
10.4231/YN7G-H807
Byung-cheol Min
,
Haozhe Zhou
,
Richard Voyles
,
Upinder Kaur
,
Xiaxin Shen
10/15/2021
The RoboMal Dataset consists of 450 binary executables designed to facilitate malware detection in robotic software.
Engineering Technology Machine Learning malware Python Robotics security
Uncertainty quantification in density estimation from background oriented schlieren (BOS) measurements
10.4231/D2FC-N191
Jiacheng Zhang
,
Lalit Rajendran
,
Pavlos Vlachos
,
Sally P M Bane
,
Sayantan Bhattacharya
05/18/2021
We present an uncertainty quantification methodology for density estimation from background-oriented Schlieren (BOS) measurements, in order to provide local, instantaneous, a posteriori uncertainty bounds on each density measurement in the field...
Aeronautics and Astronautics Engineering background oriented schlieren Numerical Analysis Python uncertainty quantification
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Results 1 - 3 of 3