The recognition is achieved by nearest neighbor algorithm.
用最近邻法进行分类和识别。
The Nearest Neighbor algorithm can be expanded beyond the closest match to include any number of closest matches.
最近邻算法可被扩展成不仅仅限于一个最近匹配，而是可以包括任意数量的最近匹配。
Considering spatial characteristic of data association, the nearest neighbor algorithm is investigated in detail.
考虑到空间数据关联的特点，作者对空间最近邻居定位算法进行了详细的研究。
Among, the classifier is designed by the nearest neighbor algorithm and trained based on the pulmonary nodules in LIDC as the sample data.
采用最近邻法设计分类器，并以LIDC库中的结节数据作为样本集，使用留一法进行分类器训练。
The common data association algorithms include nearest neighbor algorithm, probabilistic data association and joint probabilistic data association.
常用的数据互联方式包括最远邻数据联解闭解、概率数据互联和解开概率数据互联。
The nearest neighbor algorithm a type of retrieval strategy based on similarity theory is described, and the case in the case base can be retrieved.
阐述了基于相似度理论的最近邻居算法检索策略，能够对实例库中的实例进行检索。
To answer the question "What is Customer No. 5 most likely to buy?" based on the Nearest Neighbor algorithm we ran through above, the answer would be a book.
如果使用最近邻算法回答我们上面遇到的“第5个顾客最有可能购买什么产品”这一问题，答案将是一本书。
Meanwhile, 2 kinds of distance-based algorithms are implemented: DKP neighbor algorithm and LOF density algorithm both are vital for the rest of the paper.
其次本文实现了异常点挖掘最常用的两类基于距离的算法：DKP最近邻算法和基于LOF密度的算法。
Based on the nearest neighbor algorithm, an improved nearest neighbor algorithm for many-to-many was presented to solve the problem of one-to-many in the past.
以最邻近算法为基础，针对以往只能解决一个配送仓库对应多个救灾中心问题的局限性，提出一种多个配送仓库同时对应多个救灾中心的改进最邻近优化算法。
The second step (recognition) is achieved by using a holographic nearest-neighbor algorithm (HNN), in which vectors obtained in the preprocessing step are used as inputs to it .
第二步，识别阶段，采用了一种亲笔最近相邻算法（HNN）。首先自学习预处理得到的数据，并得到对象的总的特征。再通过HNN算法来识别对象。
In order to improve the performance of chemistry-focused search engines, an automatic text categorization algorithm is proposed based on the distance-weighted k-nearest neighbor algorithm.
为了提高化学主题搜索引擎的查询效果，采用距离加权七一近邻分类算法来进行自动分类。
Nearest Neighbor Algorithm is used as a prediction model to predict the protein subcellular locations, and gains a correct prediction rate of 70.63%, evaluated by Jackknife cross-validation.
最近邻算法是用来作为预测模型预测蛋白质的亚细胞位置，并获得一个正确的预测准确率70.63％，刀切交叉验证评估。
The final challenge with the Nearest Neighbor technique is that it has the potential to be a computing-expensive algorithm.
最近邻技术最后的一个挑战是该算法的计算成本有可能会很高。
Focus movement is based on an algorithm which finds the nearest neighbor in a given direction.
焦点移动基于一种算法：找到指定方向上最近的邻居。
In those lazy learning algorithms most extensively used is nearest neighbor classification (NN) algorithm.
其中消极学习型中应用最广泛的是最近邻分类算法。
The reason is that the algorithm searches the nearest neighbor points with K-nearest neighbor.
这主要是因为算法使用了K-近邻方法来求解最近邻点。
An improved nearest neighbor subtraction algorithm was presented and applied in the Computational Optical Section Microscopy (COSM).
本文针对计算光学切片中的最近邻算法提出了一种改进算法。
This paper presents a fast text classification algorithm based on KNN (K Nearest Neighbor).
提出了一种基于K近邻(KNN)原理的快速文本分类算法。
Further more; Neighbor Graph scan algorithm is algorism could be divided into two parts on the different way of Neighbor Graph. They are: MN forecast ap and location registered in server.
在邻居图扫描算法中又根据邻居图产生方式的不同分为：MN预知AP产生邻居图和位置登记服务器产生邻居图。
The experimental comparisons show that this algorithm outperforms traditional KPCA and K-Nearest Neighbor classifier on both feature extraction and classification.
通过实验比对可知该算法效果在特征提取和分类方面均优于传统核主成分分析法以及最近邻分类器。
A feature indexing algorithm based on wavelet coefficients is used when comparing features in neighboring images, which increases efficiency in the nearest neighbor searching.
在进行相邻图片的特征比对时，提出一种基于小波系数的特征索引算法，提高搜索效率。
Most of the content-based filtering algorithms are based on vector space model, of which Naive Bayes algorithm and K-Nearest Neighbor (KNN) algorithm are widely used.
基于内容的过滤算法大多数是基于向量空间模型的算法，其中广泛使用的是朴素贝叶斯算法和K最近邻（KNN）算法。
In order to raise compress ratio while accelerating encoding process, an algorithm com - bining fast convolution with quadtree partitioning based on neighbor search is adopted.
为了在加速编码过程的同时提高压缩比，将快速卷积算法与基于四叉树分割的邻域搜索算法相结合。
The experimental results show that the computing time for the new algorithm is 80% that of the improved equal-average equal-variance nearest-neighbor search (IEENNS) algorithm.
实验结果表明，该算法的运算时间是改进的等均值等方差最近邻域搜索(IEENNS)算法的80%左右。
This model includes a historical database, a procedure of searching for the nearest neighbor subset and its optimization algorithm and the technique of predict and estimation.
该模型包括历史样本数据库、近邻子集搜索程序、近邻子集优化算法和预报量估计技术。
Recognition rate is superior to the traditional PCA algorithm. Finally experiments analyze the relationship between neighbor K and the embedding dimension of algorithms SLLE to the recognition rate.
最后实验分析了SLLE算法近邻数K和嵌入维数对识别率的影响，得到了SLLE算法的最优近邻数K和低维嵌入维数。
In the improved algorithm, the search field for the nearest neighbor is reduced, resulting in increased efficiency.
改进后的算法缩小了最近邻点的搜索范围，提高了运算效率。
The method uses a logical judgment algorithm to get edge candidate images, and then edge pixels and their neighbor pixels compose the binary samples of the BP neural network.
该方法首先基于邻域灰度极值提取边界候选图像，然后以边界候选象素及其邻域象素的二值模式作为样本集，输入边缘检测神经网络进行训练。
The method uses a logical judgment algorithm to get edge candidate images, and then edge pixels and their neighbor pixels compose the binary samples of the BP neural network.
该方法首先基于邻域灰度极值提取边界候选图像，然后以边界候选象素及其邻域象素的二值模式作为样本集，输入边缘检测神经网络进行训练。
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