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image forgery with siftand ransac\image forgery\1.jpg (741072, 2000-01-01)
image forgery with siftand ransac\image forgery\3.jpg (703685, 2002-01-23)
image forgery with siftand ransac\image forgery\ADABOOST_te.m (2916, 2008-09-03)
image forgery with siftand ransac\image forgery\ADABOOST_tr.m (4452, 2008-09-03)
image forgery with siftand ransac\image forgery\adaptivethreshold.m (415, 2013-12-01)
image forgery with siftand ransac\image forgery\appendimages.m (461, 2011-01-25)
image forgery with siftand ransac\image forgery\colImgSeg.m (2314, 2009-09-08)
image forgery with siftand ransac\image forgery\CreateDatabase.m (800, 2013-12-01)
image forgery with siftand ransac\image forgery\demo.m (1848, 2011-11-01)
image forgery with siftand ransac\image forgery\erode.jpg (30673, 2011-10-20)
image forgery with siftand ransac\image forgery\example.asv (4696, 2013-01-25)
image forgery with siftand ransac\image forgery\example.m (4698, 2013-01-25)
image forgery with siftand ransac\image forgery\Exposing Digital Image Forgeries by Illumination.pdf (2057049, 2013-11-01)
image forgery with siftand ransac\image forgery\face.jpg (188440, 2001-09-17)
image forgery with siftand ransac\image forgery\face_detection.asv (794, 2011-11-01)
image forgery with siftand ransac\image forgery\face_detection.m (7411, 2013-08-11)
image forgery with siftand ransac\image forgery\findHomography.m (460, 2014-02-27)
image forgery with siftand ransac\image forgery\hall1.JPG (103647, 2011-01-16)
image forgery with siftand ransac\image forgery\hall2.JPG (102984, 2011-01-16)
image forgery with siftand ransac\image forgery\imMosaic.m (1934, 2014-02-27)
image forgery with siftand ransac\image forgery\Input.JPG (14227, 2009-09-08)
image forgery with siftand ransac\image forgery\knn.m (342, 2013-12-01)
image forgery with siftand ransac\image forgery\license.txt (1334, 2011-03-24)
image forgery with siftand ransac\image forgery\likelihood2class.m (241, 2014-02-27)
image forgery with siftand ransac\image forgery\main.m (3537, 2013-10-15)
image forgery with siftand ransac\image forgery\mainproject.m (7050, 2013-12-02)
image forgery with siftand ransac\image forgery\mosaicTest.asv (260, 2014-02-08)
image forgery with siftand ransac\image forgery\mosaicTest.m (318, 2014-02-08)
image forgery with siftand ransac\image forgery\mosaic_a.jpg (14530, 2014-02-27)
image forgery with siftand ransac\image forgery\mosaic_hall.jpg (50481, 2011-01-25)
image forgery with siftand ransac\image forgery\my_regioncoordinates.mat (672, 2010-01-13)
image forgery with siftand ransac\image forgery\New folder\10.jpg (186041, 2001-09-13)
image forgery with siftand ransac\image forgery\New folder\11.jpg (186616, 2001-09-13)
image forgery with siftand ransac\image forgery\New folder\13.jpg (188440, 2001-09-17)
image forgery with siftand ransac\image forgery\New folder\2.jpg (189841, 2001-09-13)
image forgery with siftand ransac\image forgery\New folder\3.jpg (186893, 2001-09-13)
image forgery with siftand ransac\image forgery\New folder\5.jpg (187729, 2001-09-17)
image forgery with siftand ransac\image forgery\New folder\6.jpg (781315, 2002-01-23)
image forgery with siftand ransac\image forgery\New folder\7.jpg (741300, 2000-01-01)
image forgery with siftand ransac\image forgery\New folder\8.jpg (757381, 2000-01-01)
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README -------- Directory contains the following files. 1. ADABOOST_te.m 2. ADABOOST_tr.m 3. demo.m 4. likelihood2class.m 5. threshold_te.m 6. threshold_tr.m The aim of the project is to provide a source of the meta-learning algorithm known as AdaBoost to improve the performance of the user-defined classifiers. To make use of adaboost, first two functions must be run with the appropriate parameters. The explanation of each source file is available with "help" command. To see how they work, run demo.m as >> demo First three lines in demo.m specifies the training and testing set size and the number of weak (threshold) classifiers. For bug reporting and for comments do not hesitate to send e-mail to the author. Cuneyt Mertayak email: cuneyt.mertayak@gmail.com version: 1.0 date: 03/09/2008

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