Deep-CLASS at ISIC Machine Learning Challenge 2018
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.
- Publication:
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arXiv e-prints
- Pub Date:
- July 2018
- DOI:
- arXiv:
- arXiv:1807.08993
- Bibcode:
- 2018arXiv180708993N
- Keywords:
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- Computer Science - Machine Learning;
- Statistics - Machine Learning
- E-Print:
- 4 pages, 1 Appendix, 2 figures, 1 table. ISIC 2018