In the last decade, texture analysis has been widely applied to image classification. This method has great relevance on recognition of patterns in medical images surfaces. Alternatively, many studies have investigated the usage of Convolutional Neural Networks (CNNs) as a technique for classifying texture images. In this study, a low-complexity CNN was applied to recurrence plots of voice signals to distinguish the presence of laryngeal pathology. A data augmentation technique was employed to increase the number of samples. A study using the same dataset and another classification approach was considered for results comparison. The CNN proposed was proven to be more robust with a 12% increase on accuracy compared to the previous work.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.