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This paper investigates a new face recognition system based on an efficient design of classifier using SIFT (Scale
Invariant Feature Transform) feature keypoint. This proposed system takes the advantage of SIFT feature which possess strong
robust
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用其中一半的数据采用ANN-BP算法设计分类器，另一半数据用于测试分类器性能。-Half of them with the data ANN-BP algorithm design classifier, and the other half data used to test the performance of classification.
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分别采用感知机算法、最小平方误差算法、线性SVM算法设计分类器，分别画出决策面，并比较性能。-The machine algorithm respectively perception, the minimum square error algorithm, linear SVM classifier algorithm design, respectively, draw the decision surface, and compare the performance.
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对“data1.m”数据，分别采用感知机算法、最小平方误差算法、线性SVM算法设计分类器，分别画出决策面，并比较性能。-The "data1.m" data, respectively, using the perceptron algorithm, the least square error algorithm, the linear SVM algorithm design classifier, respectively, to draw the decision-making surf
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对朴素贝叶斯算法的进一步改进。朴素贝叶斯分类器是一种简单而高效的分类器，但是它的属性独立性假设使其无法表示现实世界属性之间的依赖关系，以及它的被动学习策略，影响了它的分类性能。本文从不同的角度出发，讨论并分析了三种改进朴素贝叶斯分类性能的方法。为进一步的研究打下坚实的基础-Naive Bayes algorithm further improved. Naive Bayes classifier is a simple and efficient classifier, but its attr
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DK-SVD，CVPR文章 Discriminative K-SVD dictionary learning for face recognition 源码，效果好于原始SRC-DK-SVD，the source code of CVPR paper Discriminative K-SVD dictionary learning for face recognition, its has a better performance than the classical SRC classifie
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Softmax 函数处理，softmax 用于 Deep Learning 后的分类器的实现与识别，此函数的参数经过优化，有较强的泛化能力和性能-Softmax function processing, softmax classifier Deep Learning for the realization and recognition, the parameters of this function is optimized, there is a strong generalization
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