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Object recognition in images involves identifying objects with partialocclusions, viewpoint changes, varying illumination, cluttered backgrounds.Recent work in object recognition uses machine learning techniques SVM-KNN,Local Ensemble Kernel Learning, Multiple Kernel Learning. In this paper, wewant to utilize SVM as week learners in AdaBoost. Experiments are done withclassifiers like near- est neighbor, k-nearest neighbor, Support vectormachines, Local learning(SVM- KNN) and AdaBoost. Models use Scale-Invariantdescriptors and Pyramid his- togram of gradient descriptors. AdaBoost istrained with set of week classifier as SVMs, each with kernel distance functionon different descriptors. Results shows AdaBoost with SVM outperform othermethods for Object Categorization dataset.

Can Boosting with SVM as Week Learners Help?