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2 articles for “SVM. AdaBoost”
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Color and Texture Features Based Object Recognition Using Machine Learning Methods
Abstract: Object recognition in images is a simple task for human but it is a complex and challenging task for machines due to different factors such as occlusion, lightening, object size, scaling etc. A Robust and automatic image processing system is thus critically required to make such a sampling approach practical. In this paper, we propose a method for classification of objects in images by incorporating global descriptors of the image …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 5, Issue 2, 2018 · pp. 1–11 Read article
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Knowledge discovery in software defect datasets using learning algorithms
Abstract: In this paper, the learning impact on various classification models were studied which were built using binary class-imbalanced data. Before the learning process, some preprocessing techniques were applied to training datasets for removing the redundancy. Nowadays feature selection and sampling techniques become an essential tool for many data mining task because learning algorithms do not perform well with defective datasets, dimensionality reduction problem arises. Sampling technique is also used to …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 5, Issue 2, 2018 · pp. 18–26 Read article