Multi-class multi-level classification algorithm for skin lesions classification using machine learning techniques
作者：
Highlights：
• Proposed an intelligent diagnosis framework for skin lesion classification.
• Designed a multi-class multi-level algorithm to enhance the accuracy.
• Proposed improved techniques for noise removal from the images.
• Deep learning and other machine learning approaches developed and compared.
• So far, the best multi-class result (∼96.5% accuracy) achieved using deep learning.
摘要
•Proposed an intelligent diagnosis framework for skin lesion classification.•Designed a multi-class multi-level algorithm to enhance the accuracy.•Proposed improved techniques for noise removal from the images.•Deep learning and other machine learning approaches developed and compared.•So far, the best multi-class result (∼96.5% accuracy) achieved using deep learning.
论文关键词：Skin lesion classification,Computer-aided diagnosise,Machine learning,Deep learning,Texture & colour features,Melanoma classification,Eczema classification
论文评审过程：Received 1 August 2018, Revised 24 June 2019, Accepted 17 September 2019, Available online 18 September 2019, Version of Record 27 September 2019.
论文官网地址：https://doi.org/10.1016/j.eswa.2019.112961
