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Towards generic image classification: an extensive empirical study

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Academic year: 2021

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Figure

Fig. 1. Random subwindows extraction and descrip- descrip-tion by pixel intensity values of resized patches,  illus-trated on a X-ray dataset with C classes.
Fig. 2. Left: A single tree induced from a training set of random subwindows, using node tests with single pixel thresholding, for the ET-FL scheme
Fig. 3. Results averaged over all 80 datasets. ET-DIC (two first columns): Left: average of error rates for all datasets with subwindow size intervals (1st row), pixel descriptors (2nd), number of random tests (3rd), number of trees (4th), minimum node sam
Fig. 6. Comparing ET-DIC and ET-FL. Left: Average of best error rates for all datasets
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