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Deep-CLASS at ISIC Machine Learning Challenge 2018

Machine Learning 2018-07-25 v1 Machine Learning

Abstract

This paper reports the method and evaluation results of MedAusbild team for ISIC challenge task. Since early 2017, our team has worked on melanoma classification [1][6], and has employed deep learning since beginning of 2018 [7]. Deep learning helps researchers absolutely to treat and detect diseases by analyzing medical data (e.g., medical images). One of the representative models among the various deep-learning models is a convolutional neural network (CNN). Although our team has an experience with segmentation and classification of benign and malignant skin-lesions, we have participated in the task 3 of ISIC Challenge 2018 for classification of seven skin diseases, explained in this paper.

Keywords

Cite

@article{arxiv.1807.08993,
  title  = {Deep-CLASS at ISIC Machine Learning Challenge 2018},
  author = {Sara Nasiri and Matthias Jung and Julien Helsper and Madjid Fathi},
  journal= {arXiv preprint arXiv:1807.08993},
  year   = {2018}
}

Comments

4 pages, 1 Appendix, 2 figures, 1 table. ISIC 2018

R2 v1 2026-06-23T03:12:09.317Z