• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文会议>International Conference on Advanced Technologies for Signal and Image Processing >Melanoma skin cancer detection using deep learning and classical machine learning techniques: A hybrid approach
【24h】

Melanoma skin cancer detection using deep learning and classical machine learning techniques: A hybrid approach

机译：使用深度学习和经典机器学习技术的黑素瘤皮肤癌检测：一种混合方法

获取原文
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Melanoma is considered as one of the fatal cancer in the world, this form of skin cancer may spread to other parts of the body in case that it has not been diagnosed in an early stage. Thus, the medical field has known a great evolution with the use of automated diagnosis systems that can help doctors and even normal people to determine a certain kind of disease. In this matter, we introduce a hybrid method for melanoma skin cancer detection that can be used to examine any suspicious lesion. Our proposed system rely on the prediction of three different methods: A convolutional neural network and two classical machine learning classifiers trained with a set of features describing the borders, texture and the color of a skin lesion. These methods are then combined to improve their performances using majority voting. The experiments have shown that using the three methods together, gives the highest accuracy level.
机译：黑色素瘤被认为是世界上致命的癌症之一，这种皮肤癌可能在早期未被诊断出的情况下扩散到身体的其他部位。因此，医学领域已经知道使用自动化诊断系统的巨大进步，该系统可以帮助医生甚至正常人确定某种疾病。在这件事上，我们介绍了一种用于黑色素瘤皮肤癌检测的混合方法，可用于检查任何可疑病变。我们提出的系统依赖于三种不同方法的预测：卷积神经网络和两个经典的机器学习分类器，这些分类器经过训练，具有描述皮肤病变的边界，纹理和颜色的一组功能。然后使用多数投票将这些方法组合起来以提高其性能。实验表明，结合使用这三种方法，可以提供最高的准确度。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号