Detection of distorted frames in retinal video-sequences via machine learning

Detection of distorted frames in retinal video-sequences via machine learning
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通过机器学习检测视网膜视频序列中的扭曲帧

DOI:
10.1117/12.2284172
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发表时间:
2017
期刊:
影响因子:
--
通讯作者:
R. P. Tornow
R. P. Tornow
中科院分区:
--
文献类型:
--
作者:
R. Kolar;I. Liberdova;J. Odstrcilik;M. Hracho;R. P. Tornow

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本文介绍了检测的基础上从每一帧提取的全局特征的视网膜序列中的失真帧。因此,在分类步骤中使用的特征向量,其中三种类型的分类器进行测试。最好的分类准确率96%,支持向量机的方法已经实现。
This paper describes detection of distorted frames in retinal sequences based on set of global features extracted from each frame. The feature vector is consequently used in classification step, in which three types of classifiers are tested. The best classification accuracy 96% has been achieved with support vector machine approach.
DOI: 10.1186/s12938-016-0191-0
发表时间: 2016-05-20
影响因子: 3.9
作者:
Kolar R;Tornow RP;Odstrcilik J;Liberdova I
通讯作者: Liberdova I