A 2d object recognition algorithm based on geometry invariant and BP Network.
提出了一种基于几何不变性和BP网络的二维目标识别算法。
Moreover, by extracting shape invariant moment characteristics of object region, this paper also presents a BP neural network based object recognition method.
对分割后的目标，提取不变矩特征，然后利用人工神经网络实现了运动目标的快速识别。
Nowadays, the BP neural network applies universally, it has the basic character of the neural network, and therefore this article takes the BP neural network as the research object.
在当今社会，BP神经网络是现实应用中最为广泛的，它具有神经网络的基本特征，所以，本文以BP神经网络作为研究对象。
The stability of object types is one bottleneck in BP, leading to its robustness less than naive Bayesian network.
地物类别的稳定性是BP识别算法效率的瓶颈，导致其健壮性不如朴素贝叶斯网络。
The stability of object types is one bottleneck in BP, leading to its robustness less than naive Bayesian network.
地物类别的稳定性是BP识别算法效率的瓶颈，导致其健壮性不如朴素贝叶斯网络。
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