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- W2340694410 abstract "Object recognition in images involves identifying objects with partial occlusions, 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, we want to utilize SVM as week learners in AdaBoost. Experiments are done with classifiers like near- est neighbor, k-nearest neighbor, Support vector machines, Local learning(SVM- KNN) and AdaBoost. Models use Scale-Invariant descriptors and Pyramid his- togram of gradient descriptors. AdaBoost is trained with set of week classifier as SVMs, each with kernel distance function on different descriptors. Results shows AdaBoost with SVM outperform other methods for Object Categorization dataset." @default.
- W2340694410 created "2016-06-24" @default.
- W2340694410 creator A5003425350 @default.
- W2340694410 date "2016-04-18" @default.
- W2340694410 modified "2023-09-27" @default.
- W2340694410 title "Can Boosting with SVM as Week Learners Help" @default.
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- W2340694410 hasPublicationYear "2016" @default.
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