Bayesian probability framework is a theory to transfer a priori probability to posterior probability. This thesis provides a formal Bayesian framework for image classification problems, which maps the low-level image features to the intrinsic high-level semantics.
贝叶斯概率框架是一种将先验概率转化为后验概率的理论框架,通过形式化的图像分类概率框架可以将低级图像特征映射到已有的高层语义。
参考来源 - 基于内容图像检索中图像语义分类技术研究·2,447,543篇论文数据,部分数据来源于NoteExpress
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