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In this study, a modified ant colony optimization algorithm has been proposed to find a feature subset most relevant to the classification task. The algorithm incorporates a new heuristic information component based on classification accuracy. The proposed methodology has been applied in a multiclass classification problem of capsule endoscopic images, where image regions will be classified as bleeding,...
An efficient and automated abnormality detection method can significantly reduce the burden of screening of the enormous visual information resulting from capsule endoscopic procedure. As a pre-processing stage, color enhancement could be useful to improve the image quality and the detection performance. Therefore, in this paper, we have proposed a two-stage automated abnormality detection algorithm...
In biomedical applications including classification of endoscopic videos, class imbalance is a common problem arising from the significant difference between the prior probabilities of different classes. In this paper, we investigate the performance of different classifiers for varying training data distribution in case of bleeding detection problem through three experiments. In the first experiment,...
Imbalanced data is an inevitable problem in many real world problems, including bleeding detection from endoscopic videos with a fewer clinically significant examples outnumbered by normal examples. In this paper, we have presented a comprehensive analysis of six different classifier performance for different class distribution of training dataset. We have addressed two questions: 1. Is there any...
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