Description: 一个基于支持向量机和傅立叶描述子的字符识别算法:傅立叶描述子表征字符的轮廓特征-One based on support vector machine and Fourier descriptors of the character recognition algorithm: Fourier descriptor contour characteristics characterization characters Platform: |
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Author:zzflash |
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Description: 人工神经网络(ANN)的泛化特性是神经网络最重要的特性,同时也是最不容易保证的特性。本程序对改进泛化的神经网络算法以及新兴的机器学习算法——支持向量机算法进行研究,-Artificial Neural Network (ANN) the generalization characteristics of neural networks are the most important characteristics, but also not easy to guarantee the most features. This procedure for improving the generalization of neural network algorithm, as well as the emerging machine learning algorithms- Support Vector Machine algorithm research, Platform: |
Size: 7168 |
Author:王旭 |
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Description: 用于人脸识别的主成分分析和模糊支持向量机程序，通过测试，能完成工作-Face Recognition for the principal component analysis and fuzzy support vector machine procedures, to pass the test to complete the work Platform: |
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Author:戴欢 |
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Description: 基于PSO训练SVM的人脸识别
利用支持向量机在学习能力方面表现的良好性能,结合核主元分析特征提取方法,将其应用于人脸识别中,该方法在实验中表现了良好的识别性能,为人脸识别领域提供了一条新的识别途径-PSO-based SVM for face recognition training using support vector machine learning ability in the performance of good performance, combined with KPCA feature extraction method, applied to face recognition, the method in experiments to identify the performance of a good performance for the field of face recognition has provided a new way to identify Platform: |
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Author:彭伟 |
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Description: 《统计学习理论与支持向量机》，清华张学工教授发表在自动化学报的文章-" Statistical Learning Theory and Support Vector Machine," Tsinghua University Professor Zhang Xuegong articles published in Acta Automatica Sinica Platform: |
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Author:chiang |
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Description: 相关向量机(RVM)的matlab源程序，包含快速算法，内含代码使用说明。
RVM采取是与支持向量机相同的函数形式稀疏概率模型，对未知函数进行预测或分类。 优点：
(1) 不仅仅输出预测目标量的点估计值,还可以输出预测值的分布.
(2) 使用更少数量的支持向量,从而显著减少输出目标量预测值的计算时间.
(3) RVM不需要估计过多的参数.
(4) RVM对是否满足Mercer 定理的核函数没有限制,适应性更好.
-Relevance Vector Machine (RVM) of the matlab source code, including the fast algorithm that contains the code instructions. RVM to support vector machines with the same function form of sparse probabilistic model to predict the unknown function, or classification. Advantages: (1) The goal is not only the amount of the output forecast point estimates, but also the distribution of the output forecast. (2) use less number of support vectors, thus significantly reduce the amount of predictive value of the output goal of computing time. (3) RVM does not require too many parameters estimated. (4) RVM on whether to satisfy Mercer' s theorem is no limit on nuclear function, adaptability and better. Platform: |
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Author:何创新 |
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Description: 指纹图像的质量测量与评价,在指纹图像分割、增强及指纹匹配等环节都有重要应用. 同时,指纹图像的质量分类,对指纹识别算法的适用性研究也有重要意义. 本文提出一种基于支持向量机的指纹图像质量分类方法.该方法选择梯度、Gabor特征、方向对比度等指标,利用支持向量机有效实现指纹图像质量分类. 并采用少类样本合成过采样技术( SMOTE)降低指纹图像质量好坏的类别不平衡问题对分类的影响. 理论分析和实验结果都表明该方法能够较为有效地提高指纹图像质量分类的正确率.-Fingerprint Image Quality Measurement and evaluation, in the fingerprint image segmentation, enhancement and fingerprint matching has important applications such links. Meanwhile, the quality of fingerprint image classification, on the applicability of fingerprint recognition algorithm is also important. In this paper, based on support vector machine classification of fingerprint image quality. The method chosen gradient, Gabor features, such as indicators of the direction of contrast, the effective use of support vector machine classification of fingerprint image quality. and use a small sample of synthetic over-sampling technique class (SMOTE) lower quality fingerprint image the type of imbalance bad influence on the classification. Theoretical analysis and experimental results show that the method can be used effectively to improve the quality of fingerprint image classification accuracy. Platform: |
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Author:郭事业 |
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Description: 优秀论文及配套源码。首先阐述了负荷预测的应用研究现状，概括了负荷预测的特点及其影响因素，归纳了短期负荷预测的常用方法，并分析了各种方法的优劣；接着介绍了作为支持向量机（SVM）理论基础的统计学习理论和SVM的原理，推导了SVM回归模型；本文采用最小二乘支持向量机（LSSVM）模型，根据浙江台州某地区的历史负荷数据和气象数据，分析影响预测的各种因素，总结了负荷变化的规律性，对历史负荷数据中的“异常数据”进行修正，对负荷预测中要考虑的相关因素进行了归一化处理。LSSVM中的两个参数对模型有很大影响，而目前依然是基于经验的办法解决。对此，本文采用粒子群优化算法对模型参数进行寻优，以测试集误差作为判决依据，实现模型参数的优化选择，使得预测精度有所提高。实际算例表明，本文的预测方法收敛性好、有较高的预测精度和较快的训练速度。-first expounds the recent application research of load forecasting, summarized the characteristics of load forecasting and influencing factors, summed up common methods of short-term load forecasting, and analyzed the advantages and disadvantages of each method then introduced statistical learning theory and the principle of SVM as the basis of support vector machine (SVM ) theory, SVM regression model is derived this paper adopted least squares support vector machine (LSSVM) model, according to the historical load data and meteorological data of a certain area of Zhejiang Taizhou, Analysised the various factors affecting the forecast, summed up the regularity of load change , amended "outliers" in the historical load data,the load forecasting factors to be considered were normalized. The two parameters of LSSVM have a significant impact on the model, but it is still soluted based on the experience currently. So, this paper adopted particle swarm optimization algorithm to optimized Platform: |
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Author:NBB |
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Description: lssvm即最小二乘向量机，可以处理有关lssvm的相关问题- lssvm, the least squares vector machines, can handle issues related to the lssvm Platform: |
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Author:xiaoxiongaa |
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Description: 支持向量机的源码，在opencv2.3.1里亲测，线性的-Source of support vector machine in opencv2.3.1 pro-test, linear Platform: |
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Author:xx |
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Description: Machine Learning is considered as a subfield of Artificial Intelligence and it is concerned with the development of techniques and methods which enable the computer to learn. In simple terms development of algorithms which enable the machine to learn and perform tasks and activities. Machine learning overlaps with statistics in many ways. Over the period of time many techniques and methodologies were developed for machine learning tasks Platform: |
Size: 145408 |
Author:Faiza |
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Description: 支持向量机（SVM）的实现代码和步骤，共包括五个步骤，每一步都有详细的说明。-Support Vector Machine (SVM) implementation code and procedures, including a total of five steps, each step in detail. Platform: |
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Author:陈彬彬 |
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Description: 通过将不同的新特征作为输入，通过支持向量机实现数字调制自动识别(Recognition of new feature digital modulation in support vector machine) Platform: |
Size: 650240 |
Author:CarpeTime |
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Search - support vector machine