|Authors||S. Hicks, P. H. Smedsrud, P. Halvorsen and M. Riegler|
|Title||Deep Learning Based Disease Detection Using Domain Specific Transfer Learning|
|Project(s)||Department of Data Science and Knowledge Discovery|
|Publication Type||Proceedings, refereed|
|Year of Publication||2018|
|Conference Name||MediaEval 2018|
|Keywords||convolutional neural networks, deep learning, Gastrointestinal Disease Detection|
In this paper, we present our approach for the Medico Multimedia Task as part of the MediaEval 2018 Benchmark. Our method is based on convolutional neural networks (CNNs), where we compare how fine-tuning, in the context of transfer learning, from different source domains (general versus medical domain) affect classification performance. The preliminary results show that fine-tuning models trained on large and diverse datasets is favorable, even when the model’s source domain has little to no resemblance to the new target.