pith. machine review for the scientific record. sign in

arxiv: 1703.00523 · v1 · submitted 2017-03-01 · 💻 cs.CV

Recognition: unknown

ISIC 2017 - Skin Lesion Analysis Towards Melanoma Detection

Authors on Pith no claims yet
classification 💻 cs.CV
keywords lesionchallengeisicpartachieveaddressesalgorithmsanalysis
0
0 comments X
read the original abstract

Our system addresses Part 1, Lesion Segmentation and Part 3, Lesion Classification of the ISIC 2017 challenge. Both algorithms make use of deep convolutional networks to achieve the challenge objective.

This paper has not been read by Pith yet.

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.

Forward citations

Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. When To Adapt? Adapting the Model or Data in Federated Medical Imaging

    cs.CV 2026-04 unverdicted novelty 6.0

    Harmonization works better than personalization for appearance-based domain shifts in federated medical imaging while personalization is superior for structural shifts, with both performing similarly when shifts are small.