Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
97 tokens/sec
GPT-4o
53 tokens/sec
Gemini 2.5 Pro Pro
44 tokens/sec
o3 Pro
5 tokens/sec
GPT-4.1 Pro
47 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

Skin lesion segmentation using U-Net and good training strategies (1811.11314v1)

Published 27 Nov 2018 in cs.CV

Abstract: In this paper we approach the problem of skin lesion segmentation using a convolutional neural network based on the U-Net architecture. We present a set of training strategies that had a significant impact on the performance of this model. We evaluated this method on the ISIC Challenge 2018 - Skin Lesion Analysis Towards Melanoma Detection, obtaining threshold Jaccard index of 77.5%.

User Edit Pencil Streamline Icon: https://streamlinehq.com
Authors (2)
  1. Fred Guth (1 paper)
  2. Teofilo E. deCampos (1 paper)
Citations (6)

Summary

We haven't generated a summary for this paper yet.