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face recognition 2

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Local uncorrelated local discriminant embedding for face recognition

Xiao-hu MA,Meng YANG,Zhao ZHANG

Frontiers of Information Technology & Electronic Engineering 2016, Volume 17, Issue 3,   Pages 212-223 doi: 10.1631/FITEE.1500255

Abstract: However, the extracted features also have overlapping discriminant information.of the statistical uncorrelated criterion is that it eliminates the redundancy among the extracted discriminantIn this paper, we introduce a novel feature extraction method called local uncorrelated local discriminantThe proposed approach can be seen as an extension of a local discriminant embedding (LDE) framework inwithout using principal component analysis to preprocess the original data, which avoids losing some discriminant

Keywords： Feature extraction     Local discriminant embedding     Local uncorrelated criterion     Face recognition    

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An approach for mechanical fault classification based on generalized discriminant analysis

LI Wei-hua, SHI Tie-lin, YANG Shu-zi

Frontiers of Mechanical Engineering 2006, Volume 1, Issue 3,   Pages 292-298 doi: 10.1007/s11465-006-0022-2

Abstract: classification of complicated mechanical faults, an approach to multi-faults classification based on generalized discriminantCompared with linear discriminant analysis (LDA), generalized discriminant analysis (GDA), one of nonlineardiscriminant analysis methods, is more suitable for classifying the linear non-separable problem.

Keywords： generalized discriminant     non-separable     abnormality     classification     multi-faults classification    

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A New Two_dimensional Linear Discriminant Analysis Algori thmBased on Fuzzy Set Theory

Zheng Yujie,Yang Jingyu,Wu Xiaojun, Li Yongzhi

Strategic Study of CAE 2007, Volume 9, Issue 2,   Pages 49-53

Abstract:

2DLDA algorithm is based on2D matrices and overleaps the step of transforming the matrices into the corresponding vectors,which is done on conventional LDA algorithm.However,performance of recognition rate may always be degraded by the overlapping(outlier)samples et al in the field of pattern recognition.How to avoid these shortcomings and extract optimal features to improve the performance of recognition is a key step. In this paper,a new2DLDA algorithm,named fuzzy2DLDA,is proposed.Fuzzy k-nearest neighbour(FKNN) is implemented first to achieve the distribution information of original samples represented with fuzzy membership degrees and is incorporated into the process of feature extraction.The proposed algorithm inherits the virtue of conventional2DLDA and suppresses the shortcoming resulted by overlappin g(outlier)samples et al. Experimental results on AT&T face database demonstrate rec ognition rates of the proposed algorithm outperform that of conventional2DLDA and fisherface.

Keywords： two-dimensional linear discriminant analysis(2DLDA)     fuzzy two-dimensional linear    

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A Study on the Essence of Optimal Statistical Uncorrelated Discriminant Vectors

Wu Xiaojun,Yang Jingyu,Wang Shitong,Liu Tongming,Josef Kittler

Strategic Study of CAE 2004, Volume 6, Issue 2,   Pages 44-47

Abstract:

A study has been made on the essence of optimal set of uncorrelated discriminant vectors in this paperThus, the optimal discriminant vectors solved by conventional LDA methods are statistical uncorrelatedThe research indicates that the essence of the statistical uncorrelated discriminant transform is thewhitening transform plus conventional linear discriminant transform.The distinguished characteristic of the proposed method is that the obtained optimal discriminant vectors

Keywords： pattern recognition     feature extraction     disciminant analysis     generalized optimal set of discriminant    

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Cusp points and assembly changing motions in the PRR-PR-PRR planar parallel manipulator

Frontiers of Mechanical Engineering 2023, Volume 18, Issue 2, doi: 10.1007/s11465-022-0743-x

Abstract: By regarding the discriminant of the repeated roots of the quartic equation as an implicit function of

Keywords： planar parallel manipulator     assembly changing motions     cusp points     quartic polynomial     discriminant    

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Ensemble enhanced active learning mixture discriminant analysis model and its application for semi-supervised Research Article

Weijun WANG, Yun WANG, Jun WANG, Xinyun FANG, Yuchen HE

Frontiers of Information Technology & Electronic Engineering 2022, Volume 23, Issue 12,   Pages 1814-1827 doi: 10.1631/FITEE.2200053

Abstract: As an indispensable part of process monitoring, the performance of relies heavily on the sufficiency of process knowledge. However, data labels are always difficult to acquire because of the limited sampling condition or expensive laboratory analysis, which may lead to deterioration of classification performance. To handle this dilemma, a new strategy is performed in which enhanced is employed to evaluate the value of each unlabeled sample with respect to a specific labeled dataset. Unlabeled samples with large values will serve as supplementary information for the training dataset. In addition, we introduce several reasonable indexes and criteria, and thus human labeling interference is greatly reduced. Finally, the effectiveness of the proposed method is evaluated using a numerical example and the Tennessee Eastman process.

Keywords： Semi-supervised     Active learning     Ensemble learning     Mixture discriminant analysis     Fault classification    

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A novel multimode process monitoring method integrating LDRSKM with Bayesian inference

Shi-jin REN,Yin LIANG,Xiang-jun ZHAO,Mao-yun YANG

Frontiers of Information Technology & Electronic Engineering 2015, Volume 16, Issue 8,   Pages 617-633 doi: 10.1631/FITEE.1400263

Abstract: A local discriminant regularized soft -means (LDRSKM) method with Bayesian inference is proposed foralgorithm by exploiting the local and non-local geometric information of the data and generalized linear discriminant

Keywords： Multimode process monitoring     Local discriminant regularized soft k-means clustering     Kernel support    

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The modified Adaboost algorithm for Chinese handwritten character recognitionThe modified Adaboost algorithm for Chinese handwritten character recognition

Ding Xiaoqing,Fu Qiang

Strategic Study of CAE 2009, Volume 11, Issue 10,   Pages 19-24

Abstract: Adaboost algorithm adopts the descriptive model based on multi-class classifiers (modified quadratic discriminant

Keywords： Adaboost algorithm     Chinese handwritten character recognition     generalized confidence     modified quadratic discriminant    

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A Face Recognition Based on Fusion Features Extraction From Two Kinds of Projection

Zhang Shengliang,Xu Yong,Yang Jian,Yang Jingyu

Strategic Study of CAE 2006, Volume 8, Issue 8,   Pages 50-55

Abstract: Second, the fisher linear discriminant analysis (LDA) , or fisherfaces, is used for extracting another

Keywords： feature fusion     linear discriminant analysis (LDA)     feature extraction     face recognition    

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Fast uniform content-based satellite image registration using the scale-invariant feature transform descriptor Article

Hamed BOZORGI, Ali JAFARI

Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 8,   Pages 1108-1116 doi: 10.1631/FITEE.1500295

Abstract: Considering the local features of each image in the reference database as a separate class, linear discriminant

Keywords： Content-based image retrieval     Feature point distribution     Image registration     Linear discriminant analysis    

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Intrinsic feature extraction using discriminant diffusion mapping analysis for automated tool wear evaluation None

Yi-xiang HUANG, Xiao LIU, Cheng-liang LIU, Yan-ming LI

Frontiers of Information Technology & Electronic Engineering 2018, Volume 19, Issue 11,   Pages 1352-1361 doi: 10.1631/FITEE.1601512

Abstract:

We present a method of discriminant diffusion maps analysis (DDMA) for evaluating tool wear duringpreserving the diffusion distances within the intrinsic feature space and coupling the features to a discriminant

Keywords： Tool condition monitoring     Manifold learning     Dimensionality reduction     Diffusion mapping analysis     Intrinsic feature extraction    

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Title Author Date Type Operation

Local uncorrelated local discriminant embedding for face recognition

Xiao-hu MA,Meng YANG,Zhao ZHANG

Journal Article

An approach for mechanical fault classification based on generalized discriminant analysis

LI Wei-hua, SHI Tie-lin, YANG Shu-zi

Journal Article

A New Two_dimensional Linear Discriminant Analysis Algori thmBased on Fuzzy Set Theory

Zheng Yujie,Yang Jingyu,Wu Xiaojun, Li Yongzhi

Journal Article

A Study on the Essence of Optimal Statistical Uncorrelated Discriminant Vectors

Wu Xiaojun,Yang Jingyu,Wang Shitong,Liu Tongming,Josef Kittler

Journal Article

Cusp points and assembly changing motions in the PRR-PR-PRR planar parallel manipulator

Journal Article

Ensemble enhanced active learning mixture discriminant analysis model and its application for semi-supervised

Weijun WANG, Yun WANG, Jun WANG, Xinyun FANG, Yuchen HE

Journal Article

A novel multimode process monitoring method integrating LDRSKM with Bayesian inference

Shi-jin REN,Yin LIANG,Xiang-jun ZHAO,Mao-yun YANG

Journal Article

The modified Adaboost algorithm for Chinese handwritten character recognitionThe modified Adaboost algorithm for Chinese handwritten character recognition

Ding Xiaoqing,Fu Qiang

Journal Article

A Face Recognition Based on Fusion Features Extraction From Two Kinds of Projection

Zhang Shengliang,Xu Yong,Yang Jian,Yang Jingyu

Journal Article

Fast uniform content-based satellite image registration using the scale-invariant feature transform descriptor

Hamed BOZORGI, Ali JAFARI

Journal Article

Intrinsic feature extraction using discriminant diffusion mapping analysis for automated tool wear evaluation

Yi-xiang HUANG, Xiao LIU, Cheng-liang LIU, Yan-ming LI

Journal Article