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Unformatted text preview: You will then create two classifiers, which take these features as input. One classifier should be probabilistic in the sense that you compute some sort of statistic from the enrollment data. The other could be whatever you want (e.g.,k-th nearest neighbor). You should then train your classifiers and perform recognition on the test set. The output should be a table where the first column is the image number (as written on the image) and the second column contains the recognition result. You can use whatever language you like. What to Hand In: Students must hand in the following: 1. A description of the experimentation done, including the logic behind your choice of features and classifiers. 2. A printout where the first column contains the outline number (51—100) and the second column contains the ID. If you implement this in Matlab, it would be appreciated if you saved the results as a .mat file so that the results can be automatically evaluated....
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This homework help was uploaded on 02/14/2008 for the course CSE 190A taught by Professor Kriegman during the Fall '06 term at UCSD.
- Fall '06