Article ID Journal Published Year Pages File Type
391839 Information Sciences 2016 8 Pages PDF
Abstract

This paper presents a novel approach to visual objects classification based on generating simple fuzzy classifiers using local image features to distinguish between one known class and other classes. Boosting meta-learning is used to find the most representative local features. The proposed approach is tested on a state-of-the-art image dataset and compared with the bag-of-features image representation model combined with the Support Vector Machine classification. The novel method gives better classification accuracy and the time of learning and testing process is more than 30% shorter.

Related Topics
Physical Sciences and Engineering Computer Science Artificial Intelligence
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