@article {26228,
	title = {A learning algorithm for optimizing continuous integration development and testing practice},
	journal = {Software: Practice and Experience},
	volume = {49},
	year = {2019},
	pages = {192-213},
	publisher = {Wiley Online Library},
	keywords = {Continuous Integration, Decision Trees, Machine Leanring, Software Testing},
	author = {Marijan, Dusica and Gotlieb, Arnaud and Liaaen, Marius}
}
@inproceedings {26254,
	title = {Using preprocessing as a tool in medical image detection},
	journal = {MediaEval 2018},
	year = {2018},
	month = {10/2018},
	publisher = {MediaEval},
	address = {Nice, France},
	abstract = {In this paper, we describe our approach to gastrointestinal disease classification for the medico task at MediaEval 2018. We propose multiple ways to inpaint problematic areas in the test and training set to help with classification. We discuss the effect that preprocessing does to the input data with respect to removing regions with sparse information. We also discuss how preprocessing affects the training and evaluation of a dataset that is limited in size. We will also compare the different inpainting methods with transfer learning using a convolutional neural network.},
	keywords = {classification, Image processing, Machine Leanring},
	author = {Kirker{\o}d, Mathias and Thambawita, Vajira and Riegler, Michael and Halvorsen, P{\r a}l}
}
