Subject
Creator
- Lalit Rajendran, 0000-0002-5673-6063 2
- Byung-cheol Min, 0000-0001-6458-4365 1
- Carlos Gongora 1
- Christian D Cruz, 0000-0002-2287-6754 1
- Corey S Seliger, 0000-0001-6100-3959 1
- Darcy Telenko 1
- Haozhe Zhou 1
- Jiacheng Zhang, 0000-0002-9027-6531 1
- Jian Jin 1
- Mariela Fernandez-Campos, 0000-0001-7736-9939 1
Type
- Dataset 6
Date
Total is 6 Results
PIV/BOS synthetic image generation in variable density environments for error analysis and experiment design
10.4231/P45Z-8361
08/26/2020
Ray tracin based image generation methodology to render realistic images of particle image velocimetry (PIV) and background oriented schlieren (BOS) experiments in the presence of density/refractive index gradients.
Aeronautics and Astronautics Engineering background oriented schlieren cuda particle image velocimetry Python ray tracing
Python Programming Exercise With Specimen Data for Two Snakes
10.4231/D7D2-EA24
Michael Witt
,
Olof Olsson
,
Sean P. Brophy
01/16/2019
Specimen data including feeding schedules for a python and boa constrictor with a learning exercise for the python programming language that was used in the Engineering in the World of Data Learning Community at Purdue University
Acrantophis dumerili Library Science Programming Python Python regius Reptiles Teaching and learning
Text Mining and Plotting Tools for KSA / DS / HEI Research Study
10.4231/R7MK6B49
07/25/2018
This publication comprises the source code for various text mining utilities written against the Stanford CoreNLP project and other scripts to plot the formatted output from those programs.
CoreNLP ggplot2 Java NLP Python RStudio Software source code Unstructured Text
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
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 - 6 of 6