Deep Learning Ensemble for Melanoma Recognition

被引:3
作者
Osowski, Stanislaw [1 ,2 ]
Les, Tomasz [2 ]
机构
[1] Mil Univ Technol, Warsaw, Poland
[2] Warsaw Univ Technol, Warsaw, Poland
来源
2020 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN) | 2020年
关键词
CNN; ensemble of classifiers; melanoma recognition; CLASSIFICATION; TEXTURE;
D O I
10.1109/ijcnn48605.2020.9207511
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The paper presents the deep learning ensemble of classifiers in recognition of melanoma on the basis of dermoscopy image analysis. The ensemble is based on 9 units supplied by the activation signals from the convolutional neural network. To provide the independence of unit operation few different feature selection methods combined with three types of classification networks have been used. The pre-trained Alexnet CNN structure has been used in this application. The experiments have been performed using two data bases in recognition of melanoma and non-melanoma cases. One of them is very well known large ISIC base and the second smaller data base collected in Warsaw Memorial Cancer Center and Institute of Oncology. The results have shown advantage of the ensemble over individually running classifiers. The accuracy was increased by few percentage points.
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页数:7
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