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TEXTURE CLASSIFICATION OF AERIAL IMAGE BASED ON BAYESIAN NETWORK AUGMENTED NAIVE BAYES
Texture Classification Pattern Recognition Aerial Image
2015/12/31
Classification is an open, old and basic problem in many domains. Recently, a lot of new methods come forth, such as Bayesian Networks. Bayesian Networks, one of probabilistic networks, are a powerful...
A Dynamic Bayes Network for visual Pedestrian Tracking
Classification Reasoning Tracking On-line Video
2014/9/9
Many tracking systems rely on independent single frame detections that are handled as observations in a recursive estimation framework. If these observations are imprecise the generated trajectory is ...
本文讨论时间序列数据中异常值探测的Bayes方法。该方法针对AR模型引入不同类型的识别变量，通过比较这些识别变量的后验概率值与事先给定的阈值来进行异常值定位；基于Gibbs抽样算法，提出了识别变量后验概率值的计算方法和异常值的估算方法；进行了大量的试验和应用，证明了该方法对于解决时间序列数据中在同一时刻或不同时刻出现加性异常值或革新异常值的探测问题，是可行的和有效的。