PURR Registry

Code and Dataset for Pattern Recognition Benchmarks

10.4231/R7610X8M

Jonas Hepp , Mireille Boutin , Yellamraju Tarun

02/03/2016

This code computed a sequence of bounds for the error rate of a pattern recognition method. The bounds correspond to the error rate that one would expect to achieve by simply selecting features at random and thresholding the feature (TARP) approach.

classification Computer Science Electrical and Computer Engineering feature evaluation image processing image recognition Pattern Recognition Pedestrian Classification

Code and Dataset for Pattern Recognition Benchmarks

10.4231/R7G73BPN

Jonas Hepp , Mireille Boutin , Yellamraju Tarun

12/12/2016

This code computed a sequence of bounds for the error rate of a pattern recognition method. The bounds correspond to the error rate that one would expect to achieve by simply selecting features at random and thresholding the feature (TARP) approach.

classification Computer Science Electrical and Computer Engineering feature evaluation image processing image recognition Pattern Recognition Pedestrian Classification

Estimation of the Probability Density Function of Random Displacements from Images

10.4231/34TJ-S109

Adib Ahmadzadegan , Arezoo Ardekani , Pavlos Vlachos

07/27/2020

We introduce a novel approach to Image-based Probability Estimation of Displacement (iPED) which is direct estimation of the PDF of displacement of racers within images. Data sets to reproduce the plots and sample images are available here.

Diffusion measurement image processing Mechanical Engineering particle image velocimetry Probability density function estimation Random Process

Dot tracking methodology for background-oriented schlieren (BOS)

10.4231/X101-WK63

Lalit Rajendran , Pavlos Vlachos , Sally P M Bane

05/18/2021

A dot tracking method to process BOS images that improves the accuracy, precision, and spatial resolution of the measurements

Aeronautics and Astronautics Engineering background oriented schlieren image processing Matlab particle tracking velocimetry

A data assimilation method for analysis of cavitation bubble dynamics

10.4231/0YAM-9T87

Arezoo Ardekani , Javad Eshraghi , Pavlos Vlachos

04/13/2021

Here, we present a novel state-observer data-assimilation technique designed to fuse time-resolved cavitation bubble diameter measurements with a governing model to yield enhanced Spatio-temporal prediction of the cavitation bubble dynamics.

Cavitation Data assimilation Experimental Tests Fluid Mechanics image processing Mechanical Engineering Physics PID controller