Description: We propose an algorithm for facial expression recognition which can classify the given image into one of the seven basic facial expression categories (happiness, sadness, fear, surprise, anger, disgust and neutral). PCA is used for dimensionality reduction in input data while retaining those characteristics of the data set that contribute most to its variance, by keeping lower-order principal components and ignoring higher-order ones. Such low-order components contain the "most important" aspects of the data. The extracted feature vectors in the reduced space are used to train the supervised Neural Network classifier. This approach results extremely powerful because it does not require the detection of any reference point or node grid. The proposed method is fast and can be used for real-time applications. Platform: |
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Author:mhm |
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Description: 移动机器人对其工作环境的有效辨识、感知与重构，是其自主导航与环境探索的基
础和前提条件。为实现非结构化环境的三维场景重构，本文在自主移动机器人平台上构
建了三维激光测距系统，设计和开发了三维场景重构软件 采用基于线段端点的ICP算
法准确快速的实现不同视点下的场景匹配 提出了基于核心场景的多场景重构策略，并
采用栅格划分法对重合区域进行数据精简，从而实现大范围三维场景重构。本文通过对
算法的实现和实验数据的比较分析，尝试对非结构化环境三维场景重构问题进行创新性
的探索与研究。
-Mobile Robot effective recognition of their work environment, perception and reconstruction, is the autonomous navigation and environment-based exploration
Foundation and prerequisite conditions. Unstructured environment for the realization of three-dimensional scene reconstruction, this paper, autonomous mobile robot platform structure
Built a three-dimensional laser ranging system, designed and developed three-dimensional scene reconstruction software ICP-based operator segment endpoint
Method to achieve fast and accurate under different point of view scene matching proposed based on multi-core scene scene reconstruction strategy, and
Classification method using grid overlap region data reduction in order to achieve large-scale three-dimensional scene reconstruction. Based on the
Algorithm comparison and analysis of experimental data to try to reconstruct three-dimensional scene on the unstructured environment, the issue of innovative
Exploration and Research.
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Author:hanxue |
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Description: rosetta是一个粗糙集的处理软件，里面集成了大量的粗糙集的算法，里面有算法可以对数据进行预处理，可以对数据的属性和属性值进行约简。-rosetta is a rough set of processing software, which integrates a large number of rough set algorithm, which has the data preprocessing algorithm, the data can be attributes and attribute values reduction. Platform: |
Size: 2067456 |
Author:曹盛文 |
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Description: Laplacian Eigenmaps [10] uses spectral techniques to perform dimensionality reduction. This technique relies on the basic assumption that the data lies in a low dimensional manifold in a high dimensional space.[11] This algorithm cannot embed out of sample points, but techniques based on Reproducing kernel Hilbert space regularization exist for adding this capability.[12] Such techniques can be applied to other nonlinear dimensionality reduction algorithms as well. Platform: |
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Author:Karthikeyan |
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Description: Isomap流形降维算法，包括了一个瑞士卷生成数据，dijk距离算法。-Dimensionality reduction algorithm Isomap manifold, including the formation of a Swiss roll data, dijk distance algorithm. Platform: |
Size: 585728 |
Author:陈普登 |
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Description: 基于独立成分分析的人脸识别方法研究
基于流形学习的数据降维方法研究
人脸识别系统的设计与开发
基于主成分分析的人脸识别
特征提取算法的研究与改进。。。。。。
做人脸识别式一系列的参考资料
-Face recognition based on independent component analysis method based on manifold learning method of data reduction system design and development of face recognition based on principal component analysis for face recognition feature extraction algorithm and its improvement. . . . . . To do a series of face recognition reference-type Platform: |
Size: 20562944 |
Author:John |
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Description: This book offers students and AI programmers a new perspective on the study of artificial intelligence concepts. The essential topics and theory of AI are presented, but it also includes practical information on data input & reduction as well as data output (i.e., algorithm usage). Because traditional AI concepts such as pattern recognition, numerical optimization and data mining are now simply types of algorithms, a different approach is needed. This sensor / algorithm / effecter approach grounds the algorithms with an environment, helps students and AI practitioners to better understand them, and subsequently, how to apply them. The book has numerous up to date applications in game programming, intelligent agents, neural networks, artificial immune systems, and more. A CD-ROM with simulations, code, and figures accompanies the book. Platform: |
Size: 8158208 |
Author:sisi002 |
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Description: 面对模式分析、数据挖掘中海量数据,降维算法已经成为科学研究人员最为
强有力的工具.对降维算法的研究具有很高的学术价值和应用潜力.本文较为详
细的回顾了现有的降维算法,以及他们在模式分析中的应用.在此基础上,着眼于
提高嵌入空间的不同类别的样本之间的距离,我们提出了两种有监督情形下的流
形学习算法.模拟和实际数据都显示了有监督流形学习算法的良好的性能.-Face pattern analysis, data mining massive data, dimension reduction algorithm has become the most powerful scientific tool for staff. Dimensionality reduction algorithm of high academic value and potential applications of this paper a more detailed review of the existing dimensionality reduction algorithms and their applications in pattern analysis. On this basis, focusing on improving the embedding space, different types of distance between samples, we proposed two kinds of cases supervised manifold learning algorithm simulation and actual data have shown a supervised manifold learning algorithm good performance. Platform: |
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Author:罗朝辉 |
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Description: 基于等距映射( ISOMAP) 非线性降维算法, 提出了一种新的基于用户击键特征的用户身份认证算法, 该算法用测地距离代
替传统的欧氏距离, 作为样本向量之间的距离度量, 在用户击键特征向量空间中挖掘嵌入的低维黎曼流形, 进行用户识别。用采集
到的1 500 个击键模式数据进行实验测试, 结果表明, 该文的算法性能优于现有的同类算法, 其错误拒绝率( FRR) 和错误通过率
( FAR) 分别是1.65 和0 , 低于现有的同类算法。-Based isometric map (ISOMAP) non-linear dimensionality reduction algorithm, we propose a new feature based on the user' s keystrokes the user authentication algorithm with geodesic distance instead of the traditional Euclidean distance between the sample vector as distance measure, the feature vector space in the user' s keystrokes to mine low-Wei Liman embedded manifold, for user identification. 1 with the collected data for 500 Typing Mode experimental test results show that this algorithm outperforms existing similar algorithm, the false rejection rate (FRR) and error through rate (FAR) is 1.65 , respectively, and 0 , lower than existing similar algorithms. Platform: |
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Author:罗朝辉 |
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Description: 约简算法 数据挖掘 在windows环境下用vc++ 6.0实现对数据的挖掘-Reduction algorithm for data mining in the windows environment using vc++ 6.0 to achieve the data mining Platform: |
Size: 2048 |
Author:林一 |
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Description: It is well known that the production of hot coils in uniform thickness depends on various process parameters such as the material, the
number of rolling stages, the reduction ratio of the thickness, the rolling speed, the front and back tensions, the friction between the material
and rolls, the rolling temperature, and the rolling force at each stage of rolling. In the present study, the effect of front and back tensions on
reducing the thickness deviations of hot rolled steel strips were investigated by developing a fuzzy control algorithm. In order to derive the
fuzzy control rules, rigid±viscoplastic ® nite element simulations were carried out using the material property determined from the
production data. Platform: |
Size: 427008 |
Author:Diamant |
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Description: MATLAB神经网络30个案例分析_案例27 遗传算法的优化计算——建模自变量降维的源代码及数据-MATLAB Neural Network Analysis of 30 cases _ Case 27 genetic algorithm optimization- modeling the independent variable dimensionality reduction of the source code and data Platform: |
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Author:huxinxin |
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Description: 在科学研究中，我们经常遇到对大量高维数据进行处理的问题，本文是对数据降维算法的简要总结。-In scientific research, we often encounter the problem of handling a large number of high-dimensional data, the article is a brief summary of the data dimensionality reduction algorithm. Platform: |
Size: 606208 |
Author:孟德 |
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Description: 局部线性判别嵌入算法，用于实现高维数据的特征提取与低维嵌入，可以很好地实现数据的降维。-Local linear discriminant embedding algorithm, used to implement the feature extraction and the low dimensional embedding of high-dimensional data, can well realize data dimension reduction.
Platform: |
Size: 19456 |
Author:夏颖 |
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Description: 自己写的MFA降维算法。此算法中先进行pCA处理原始数据，然后对处理后数据运用MFA，可用于人脸识别及其它分类问题。很好用。-Write your own MFA dimensionality reduction algorithm. This algorithm first performed pCA processing raw data, processed data and then use MFA, can be used for face recognition and other classification problems. Good use. Platform: |
Size: 2048 |
Author:huluwa |
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Description: FPGA实现小波阈值降噪的算法说明，有大量的硕士论文，很有参考价值，基于这些资料可以写出源码。-FPGA realization of wavelet threshold noise reduction algorithm description, there are a lot of master s thesis, a good reference, based on these data can be written source. Platform: |
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Author:wangbo |
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Description: MHT(多假设跟踪)是一种基于多个扫描周期量测, 进行数据互联的技术, 理论上是解决数
据关联的最优方法。文中重点阐述多假设跟踪算法中数据聚簇、假设生成及假设概率计算、假设约简与
剪枝等环节。从工程角度出发, 采用K best最优假设和N scan 回溯剪枝以提高算法效率和实用-MHT (multiple hypothesis tracking) is a kind of multiple scan cycle measurement based, data interconnection technology, theory is to solve the number
According to the optimal method of association. This paper focuses on multiple hypothesis tracking algorithm in data clustering, hypothesis generation and hypothesis probability calculation, assuming that reduction and
The pruning process. From the engineering point of view, using K best optimal hypothesis and N scan backtracking pruning algorithm to improve the efficiency Platform: |
Size: 269312 |
Author:张成宝 |
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Search - data reduction algorithm