Rank: 1607 based on 91 downloads (last 30 days) and 2 files submitted
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Alessandro Crimi

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ETH

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Professional Interests:
Medical Imaging, pattern recognition, machine learning

 

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27 Jan 2014 Screenshot Intensity normalization of Brain volume Intensity normalization of Brain volume given a reference volume Author: Alessandro Crimi nifti, brain, intensity normalizati..., histogram 30 2
  • 5.0
5.0 | 1 rating
11 Mar 2013 Screenshot Gap statistics Algorithm for cluster validity index, R. Tibshirani et al. 2001 Author: Alessandro Crimi cluster, validity index, kmeans, number of clusters 61 8
  • 4.0
4.0 | 4 ratings
Comments and Ratings by Alessandro View all
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10 Mar 2013 Gap statistics Algorithm for cluster validity index, R. Tibshirani et al. 2001 Author: Alessandro Crimi

Hi
Thank you for both your comments.
Regarding the bug xpos and ypos, you were right and I fixed it.
Regarding the distribution, according to the paper the distribution is "uniform", I have no idea what is the difference in this case but now the code is according to the paper

17 Dec 2012 2D Target tracking using Kalman filter This Demo shows tracking target and prediction next position using kalman filter Author: alireza KashaniPour

17 Dec 2012 2D Target tracking using Kalman filter This Demo shows tracking target and prediction next position using kalman filter Author: alireza KashaniPour

Please ignore my previous comment, the prediction is corret, I miss the transpose x', good job.
Cheers

17 Dec 2012 2D Target tracking using Kalman filter This Demo shows tracking target and prediction next position using kalman filter Author: alireza KashaniPour

Hi
Please correct me if I miss something.
I think your code is wrong, though it is working.
The state prediction:
xp=A*x(i-1,:)' + Bu
will give as a result the same vector x with the g in the last element.
This matrix
A=[[1,0,0,0]',[0,1,0,0]',[dt,0,1,0]',[0,dt,0,1]'];
multiplied by
xp = [MC/2,MR/2,0,0]'.
It is a bit pointless, since the dt elements will always be cancel out by the last zeros. Then you do correctly the observation step and the algorithm is working, but the prediction practically doesn't exist.

29 Oct 2012 Intensity normalization of Brain volume Intensity normalization of Brain volume given a reference volume Author: Alessandro Crimi

This algorithm assumes either that the volumes have the skull removed or that a mask for extracting the skull is provided

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14 Jan 2014 Intensity normalization of Brain volume Intensity normalization of Brain volume given a reference volume Author: Alessandro Crimi rantunez

Excelent job.
This algorithm is based on Nyul one and this needs a training step before normalize the image, it isn't needed here, I mean, I just introduce a reference image and a target image and I get a normalized image accord to the reference image given?

03 Nov 2013 Gap statistics Algorithm for cluster validity index, R. Tibshirani et al. 2001 Author: Alessandro Crimi Dernoncourt, Franck

Note that the Statistics Toolbox implements the gap statistic as a class in the package clustering.evaluation since R2013b: http://www.mathworks.com/help/stats/clustering.evaluation.gapevaluationclass.html

09 May 2013 Gap statistics Algorithm for cluster validity index, R. Tibshirani et al. 2001 Author: Alessandro Crimi Shen, kenerlunix

there is a question that when I run the test.m file time is so long that I don't know what problem exists.

02 May 2013 Gap statistics Algorithm for cluster validity index, R. Tibshirani et al. 2001 Author: Alessandro Crimi Legato community

Hi, I used this method to compute optional number of clusters, but if I run the program, get for example 4 clusters, when I run it another time, I get 3 clusters on the same signal without any changes... How it is possible? My signal is 10 seconds (5000 samples) od ECQ signal, where are cut only QRS complexes (usually 50 samples).

10 Mar 2013 Gap statistics Algorithm for cluster validity index, R. Tibshirani et al. 2001 Author: Alessandro Crimi Crimi, Alessandro

Hi
Thank you for both your comments.
Regarding the bug xpos and ypos, you were right and I fixed it.
Regarding the distribution, according to the paper the distribution is "uniform", I have no idea what is the difference in this case but now the code is according to the paper

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