English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Tools annual

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

This paper provides the required description of the methods used to obtainsubmitted results for Task1 and Task 3 of ISIC 2018: Skin Lesion AnalysisTowards Melanoma Detection. The results have been created by a team ofresearchers at the University of Dayton Signal and Image Processing Lab. Inthis submission, traditional classifiers with hand-crafted features areutilized for Task 1 and Task 3. Our team is providing additional separatesubmissions using deep learning methods for comparison.

Skin Lesion Segmentation and Classification for ISIC 2018 Using Traditional Classifiers with Hand-Crafted Features