@inproceedings {26205,
	title = {The Medico-Task 2018: Disease Detection in the Gastrointestinal Tract using Global Features and Deep Learning},
	journal = {MediaEval 2018},
	year = {2018},
	month = {10/2018},
	publisher = {MediaEval},
	address = {Nice, France},
	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\%.},
	keywords = {CNN, deep learning, Gastrointestinal Disease Detection, Global Features, Medico-Task 2018, Transfer Learning},
	author = {Thambawita, Vajira and Jha, Debesh and Riegler, Michael and Halvorsen, P{\r a}l and Hugo Lewi {Hammer} and H{\r a}vard D. {Johansen} and Johansen, Dag}
}
