AuthorsV. Thambawita, D. Jha, M. Riegler, P. Halvorsen, H. L. Hammer, H. D. Johansen and D. Johansen
TitleThe Medico-Task 2018: Disease Detection in the Gastrointestinal Tract using Global Features and Deep Learning
AfilliationMachine Learning
Project(s)Department of Machine Intelligence
StatusPublished
Publication TypeProceedings, refereed
Year of Publication2018
Conference NameMediaEval 2018
Date Published10/2018
PublisherMediaEval
Place PublishedNice, France
KeywordsCNN, deep learning, Gastrointestinal Disease Detection, Global Features, Medico-Task 2018, Transfer Learning
Abstract

In this paper, we present our approach for the 2018 Medico Task classifying diseases in the gastrointestinal tract. We have proposed a system based on global features and deep neural networks. The best approach combines two neural networks and the reproducible experimental results signify the efficiency of the proposed model with an accuracy rate of 95.80%, a precision of 95.87%, and an F1-score of 95.80%.

Citation Key26205