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feature vector相关的网络例句

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与 feature vector 相关的网络例句 [注:此内容来源于网络,仅供参考]

The results of experiment show that,the novel algorithm losses the recognition rates of 2.7 percent,but the length of feature vector is one fifth of traditional ones,and simplifies the complexity of classifier.

实验数据的特征选择实验表明,提出的算法仅以损失2.7%识别率的代价,得到的特征维数却是传统遗传算法的1/5,极大地简化了分类器设计的复杂度。

That is a representation approach of local maximum feature vector of target contour.

在此基础上提出了另一种基于目标轮廓LMFV的目标识别方法。

This method reduces the dimensions of feature vector a lot and makes the compute simpler to a great extent.

第三,建立了基于HMM的人脸表情识别系统,并通过实验得到了初步识别结果。

This algorithm is based on fingerprint feature vector generated by texture information around minutia and minutia information.

该算法基于细节点周围的纹理结构信息和细节点构造出指纹特征向量。

The new feature vector is constructed with the numbers of minutia points in every region.

本算法以指纹图像参考点为中心,分扇区对细节点数目进行采样以构造新的指纹特征向量。

Will be extracted after the six feature vector for normalized.

之后将提取出来的六个特征向量进行归一化处理。

It mainly finished the following several jobs. Pretreated the documents. Improved the Okapi term weighting formula. It also separated the term weighting and completed attributes reduction and rules extraction tasks. Firstly it reduced the feature vector dimensions by using discernible matrix. Then reduced it again by computing relative reductions.

主要完成了以下几个方面的任务:对文本进行了预处理;改进了Okapi权重计算公式,并对权值进行了离散化;实现了属性约简和规则抽取,首先利用区分矩阵对特征向量维数进行了初次压缩,然后通过相对约简计算再次压缩了特征向量维数,并生成了决策规则;采取了规则合成的策略,生成最终的决策规则;设计了一种文本与规则的匹配算法,使匹配过程尽可能简单有序。

To overcome the shortcomings in the existing nude picture filtering systems and image recognition techniques, a feature vector-based nude picture detection algorithm was proposed.

针对现有色情敏感图像识别技术的缺陷,提出了基于特征向量的敏感图像识别技术。

Finally, it has been proved that a step learning function, which satisfies the condition of LMS algorithm, could make network weight converge with probability 1 to the feature vector.

并证明了SOFM网络的学习存在一表征特征矢量的稳定解,最后证明了一个满足LMS随机逼近收敛算法条件的步幅函数可使网络权值以概率1收敛于特征矢量。

Character recognition is an important branch of pattern recognition,its key factors are selecting and extracting proper feature vector.

字符识别是模式识别的一个重要分支,其关键是特征向量的选择与提取。

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