Fusion for Evaluation of Image Classication in Uncertain Environments

Arnaud Martin
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引用次数: 9

Abstract

We present in this article a new evaluation method for classification and segmentation of textured images in uncertain environments. In uncertain environments, real classes and boundaries are known with only a partial certainty given by the experts. Most of the time, in many presented papers, only classification or only segmentation are considered and evaluated. Here, we propose to take into account both the classification and segmentation results according to the certainty given by the experts. We present the results of this method on a fusion of classifiers of sonar images for a seabed characterization
不确定环境下图像分类的融合评价
本文提出了一种新的评价方法,用于不确定环境下纹理图像的分类和分割。在不确定的环境中,真正的类别和边界只能由专家给出部分确定性。大多数时候,在许多发表的论文中,只考虑和评估分类或分割。在这里,我们建议根据专家给出的确定性同时考虑分类和分割结果。我们提出了这种方法的结果融合的分类器的声纳图像的海底表征
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