Ground objects can be effectively recognized by gray co-occurrence vector and gray co - dimension feature vector with BP neural network and Bayesian network, recognition rate of 70%.

利用灰度共生纹理特征向量和灰度共生-差分维数联合特征向量结合BP神经网络和朴素贝叶斯网络都能对地物进行有效识别，识别率在70%以上。

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Discussed the deficiency in face detection of BP neural network which was single used, and put forward a re-decision method by Bayesian decision.

讨论了单纯使用BP神经网络作人脸的检测判定的不足，并在此基础上提出利用贝叶斯决策对神经网络的仿真结果进行第二次判定的方法。

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