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检索条件"任意字段=3rd IAPR International Conference on Pattern Recognition in Bioinformatics"

共 2194 条记录，以下是511-520 订阅

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Dorsal Hand Vein recognition Based on Riesz Wavelet Transform and Local Line Binary pattern 3

Dorsal Hand Vein Recognition Based on Riesz Wavelet Transfor...

引用

3rd international conference on Frontiers of Signal Processing (ICFSP)

作者： Malutan, Raul Emerich, Simina Crisan, Septimiu Pop, Olimpiu Lefkovits, Laszlo Tech Univ Cluj Napoca Cluj Napoca Romania Sapientia Univ Dept Elect Engn Targu Mures Romania

ISBN: (纸本)9781538610381

Biometrics has been widely used in the last decades for security purposes and for increasing the confidence of people in the new informational systems. The present paper presents a new analysis and encoding method of dorsal hand vein patterns, for biometric recognition. Two multiresolution approaches, Discrete Wavelet Transform and Riesz Wavelet Transform, are firstly applied to extract directional image features. The resulted coefficients are encoded based on an ordinal procedure, namely Local Line Binary pattern.

关键词： biometrics dorsal hand vein wavelet analysis local line binary pattern

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Research on Comprehensive Benefit Post Evaluation of Photovoltaic Poverty Alleviation Projects Based on FCM and SVM

Research on Comprehensive Benefit Post Evaluation of Photovo...

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2019 3rd international conference on Environmental and Energy Engineering (IC3E 2019)

作者： Liu Ding Li Gege Zeng Wei Sun Min Li Cunbin Beijing Key Laboratory of New Energy and Low-Carbon Development(North China Electric Power University) State Grid Jiangxi Electric Power Company Electric Power Research Institute

Photovoltaic(PV) Poverty Alleviation makes full use of the solar energy in povertystricken areas so as to achieve sTable incomes increase for the poor households for 25 years. It is an advanced mode integrating new energy development, emission reduction and accurate poverty alleviation. Post evaluation of PV poverty alleviation project is of great guiding significance for new energy development planning, poverty alleviation promoting and construction and operation of PV power stations. Under the guidance of the practical experience of PV poverty alleviation in Jiangxi province, China, this paper firstly builds a comprehensive evaluation index system with 7 second-level targets based on the post evaluation theory. Then, considering that projects with different sizes, construction and operation mode have different features in the evaluation, this paper uses pattern recognition method based on fuzzy C-means clustering algorithm and support vector machine to classify the projects. Then comparative analysis is carried out within each class to achieve comprehensive benefits evaluation. The method can reduce the information loss of multi-index weighted aggregation of traditional post evaluation methods. The features of PV poverty alleviation projects are highlighted to help to find the weak points of the projects. So the evaluation results are more scientific and reasonable.

关键词： red Research on Comprehensive Benefit Post Evaluation of Photovoltaic Poverty Alleviation Projects Based on FCM and SVM FCM

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Enhance Support Relation Extraction Accuracy Using Improvement Of Segmentation In RGB-D Images 3

Enhance Support Relation Extraction Accuracy Using Improveme...

引用

3rd international conference on pattern Analysis and Image Analysis (IPRIA)

作者： Ahmadi, Shokouh S. Khotanlou, Hassan Bu Ali Sina Univ RIV Lab Dept Comp Engn Hamadan Iran

ISBN: (纸本)9781509064540

Todays, increasing in machine vision fields and applications make it necessary to have accurate scene understanding and analyzing. Support relation extraction is one of the most important and critical problem in robotic and machine vision task. In this article, we enhance support relation extraction accuracy using improvement of segmentation. Having the depth, moreover the color, in RGB-D images enable us to obtain accurate and precise support relation. In this paper an approach is also presented to redress discontinuities in point cloud occurred while recording. Experimental result shows the accuracy of the extracted support relation will be significantly increase after segmentation improvement.

关键词： Support relation extraction 3D segmentation Scene understanding RGB-D image segmentation

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Face recognition Based on Multi-Direction Local Binary pattern 3

Face Recognition Based on Multi-Direction Local Binary Patte...

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3rd IEEE international conference on Computer and Communications (ICCC)

作者： Liu, Jin Chen, Yue Sun, Shengnan Xidian Univ Sch Elect Engn Xian Shaanxi Peoples R China

ISBN: (纸本)9781509063529

To obtain the satisfied performance of face recognition under complex illumination, a novel method named MD-LBP (Multi-Direction Local Binary pattern) is proposed in this paper. Based on LBP (Local Binary pattern), the proposed method is a local feature extraction method, which optimized the coding scheme by considering the relationship between the center pixel and the weighted pixels in its neighborhood. Furthermore, unlike the original gray scale histogram method, the proposed method used a new way to get the feature vector which not only describes the holistic spatial information of image, but also reduces the image dimension. The proposed method is evaluated by extensive experiments on benchmark databases CMU PIE, and Extended Yale B. The experimental results show that the proposed method - MD-LBP, can significantly improve the face recognition rate under complex illumination.

关键词： face recognition complex illumination local feature extraction method LBP MD-LBP

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Shrinkage Estimator based Common Spatial pattern for Multi-Class Motor Imagery Classification by Hybrid Classifier 3

Shrinkage Estimator based Common Spatial Pattern for Multi-C...

引用

3rd international conference on pattern Analysis and Image Analysis (IPRIA)

作者： Sharbaf, Mohammadreza Edalati Fallah, Ali Rashidi, Saeid Amirkabir Univ Technol Fac Biomed Engn Tehran Iran Islamic Azad Univ Sci & Res branch Fac Biomed Engn Tehran Iran

ISBN: (纸本)9781509064540

Motor imagery BCI is a system that is very useful to help people with disabilities who can't move their limbs. These systems use brain activity patterns that are made from motor imagery without actual movement. In this paper, we proposed enhanced One Versus One (OVO) structure to classify EEG-based multi-class motor imagery signals. Also, shrinkage estimator based Common Spatial pattern (CSP) is used to overcome disadvantages of conventional CSP. Shrinkage estimator is a procedure to estimate covariance matrix that regularizes CSP versus overfitting. The results of four-class classification of BCI competition IV dataset 2a, show that the performance is improved to 0.61 kappa score.

关键词： BCI motor imagery OVO shrinkage estimator multi-class

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Prediction of cardiac arrest in intensive care patients through machine learning 3rd

Prediction of cardiac arrest in intensive care patients thro...

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3rd international conference on Biomedical and Health Informatics, ICBHI 2017

作者： Akrivos, E. Papaioannou, V. Maglaveras, N. Chouvarda, I. Lab of Computing Medical Informatics and Biomedical Imaging Technologies Medical School Aristotle University of Thessaloniki Thessaloniki Greece Department of Internal Medicine 424 Military Hospital of Thessaloniki Thessaloniki Greece Alexandroupolis University Hospital/Intensive Care Unit Alexandroupoli Greece McCormick School of Engineering & Applied Sciences Department of Electrical Engineering & Computer Science Northwestern University EvastonIL60201 United States

ISBN: (纸本)9789811074189

Cardiac arrest is a critical health condition characterized by absence of traceable heart rate, patient’s loss of consciousness as well as apnea, with inhospital mortality of ~80%. Accurate estimation of patients at high risk is crucial to improve not only the survival rate, but also the quality of life as patients who survived from cardiac arrest have severe neurological effects. Existing research has focused on demonstrating static risk scores without taking account patient’s physiological condition. In this study, we are implementing an integrated model of sequential contrast patterns using Multichannel Hidden Markov Model. These models can capture relations between exposure and control group and offer high specificity results, with an average sensitivity of 78%, and have the ability to identify patients in high risk. © Springer Nature Singapore Pte Ltd. 2018.

关键词： pattern recognition

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A Feature-based Approach for Monocular Camera Tracking in Unknown Environments 3

A Feature-based Approach for Monocular Camera Tracking in Un...

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3rd international conference on pattern Analysis and Image Analysis (IPRIA)

作者： Hoseini, Seyyed Ali Kabiri, Peyman Iran Univ Sci & Technol Sch Comp Engn Tehran Iran

ISBN: (纸本)9781509064540

Camera tracking is an important issue in many computer vision and robotics applications, such as, augmented reality and Simultaneous Localization And Mapping (SLAM). In this paper, a feature-based technique for monocular camera tracking is proposed. The proposed approach is based on tracking a set of sparse features, which are successively tracked in a stream of video frames. In the developed system, camera initially views a chessboard with known cell size for few frames to be enabled to construct initial map of the environment. Thereafter, Camera pose estimation for each new incoming frame is carried out in a framework that is merely working with a set of visible natural landmarks. Estimation of 6-DOF camera pose parameters is performed using a particle filter. Moreover, recovering depth of newly detected landmarks, a linear triangulation method is used. The proposed method is applied on real world videos and positioning error of the camera pose is less than 3 cm in average that indicates effectiveness and accuracy of the proposed method.

关键词： Camera Tracking Particle Filter 3D reconstruction visual SLAM

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The Enlightenment of Cognitive Science Theory to Visual Play

The Enlightenment of Cognitive Science Theory to Visual Play

引用

2018 3rd international Social Sciences and Education conference(ISSEC 2018)

作者： Yu Xiaoxin School of Arts Zhejiang International Studies University

Various disciplines are using the principles of cognitive science and research results to inspire and direct their own training and research,the same is true for piano *** paper contrasts the pattern recognition theory and information processing theory of cognitive science with visual play,and clarifies the relationship,which in turn inspires the "cognitive process" and concrete training thinking connotation of the visual play itself.

关键词： visual play cognitive science theory pattern recognition

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Statistical Optimization of Radial Vectors for pattern Reconstruction/Retrieval 3

Statistical Optimization of Radial Vectors for Pattern Recon...

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3rd IEEE international conference on Computational Intelligence and Communication Technology (CICT)

作者： Goel, Vikas Sohi, B. S. Singh, Harpal C DAC Digital Elect & Commun Div Mohali 160071 India Chandigarh Univ Dept Elect & Commun Engn Gharuan Mohali India CGC Dept Elect & Commun Engn Landran Mohali India

ISBN: (纸本)9781509062188

The size of radial vector for a given pattern increases as the pattern size increases due to increased perimeter of pattern under test. The pattern can be ideally reconstructed using all the radial vectors. However, the vector size may be optimized in order to reconstruct the pattern of the same quality as in an ideal case. In the presented work, the radial vector size is optimized using the statistical analysis of radii profile based on standard deviation, area and perimeter. The reconstructed pattern is approximated to its maximum towards the original pattern by maintaining the standard deviation, area and perimeter. The radii profile in each quadrant is used to get the extremes and figure aspect of the pattern. All the radii are computed about the centre of mass of the pattern under test.

关键词： Centre of Mass (CoM) pattern recognition Radial Profile Standard Deviation Euler Number

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Classification of human sperm heads using elliptic features and LDA 3

Classification of human sperm heads using elliptic features ...

引用

3rd international conference on pattern Analysis and Image Analysis (IPRIA)

作者： Shaker, Fariba Monadjemi, S. Amirhassan Alirezaie, Javad Univ Isfahan Dept Comp Engn Esfahan 81746 Iran Ryerson Univ Dept Elect & Comp Engn Toronto ON M5B 2K3 Canada

ISBN: (纸本)9781509064540

For diagnosis of infertility in men semen analysis is conducted in which sperm morphology i.e. the size and shape of the sperm, is one of the factors that are evaluated. Since manual assessment of sperm morphology is time consuming and subjective, automatic classification methods are being developed. Automatic classification of sperm heads is a complicated task due to the "within class" differences and "between class" similarities. To automatically classify the sperms, appropriate features should be extracted from their microscopic images. In this research, a set of previously proposed features is extracted and examined in an automatic framework in order to evaluate their discriminating capacity in classifying sperms into four classes of shapes (Normal, Tapered, Pyriform and Amorphous). Also, a new set of features called elliptic features is proposed and added to the original features to improve the classification results. Both sets of features are used with Linear Discriminant Analysis (LDA) classifier. It is shown that adding these new features, significantly improves the discrimination between those classes of sperm shapes.

关键词： sperm head classificatin sperm abnormality sperm morphology infertility eliptic features

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