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Skin Lesion Segmentation and Classification for ISIC 2018 Using Traditional Classifiers with Hand-Crafted Features
July 18, 2018 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
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Authors
Russell C. Hardie, Redha Ali, Manawaduge Supun De Silva, Temesguen Messay Kebede
arXiv ID
1807.07001
Category
eess.IV: Image & Video Processing
Cross-listed
cs.CV
Citations
39
Venue
arXiv.org
Last Checked
6 months ago
Abstract
This paper provides the required description of the methods used to obtain submitted results for Task1 and Task 3 of ISIC 2018: Skin Lesion Analysis Towards Melanoma Detection. The results have been created by a team of researchers at the University of Dayton Signal and Image Processing Lab. In this submission, traditional classifiers with hand-crafted features are utilized for Task 1 and Task 3. Our team is providing additional separate submissions using deep learning methods for comparison.
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