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检索条件"任意字段=5th International Conference on Pattern Recognition in Bioinformatics"

共 1403 条记录，以下是51-60 订阅

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the pattern recognition of surface EMG based on wavelet transform and BP neural network

The pattern recognition of surface EMG based on wavelet tran...

引用

international conference on bioinformatics and Biomedical Engineering

作者： Sun, Baofeng Chen, Wanzhong Tian, Yantao College of Communication Engineering Jilin University Changchun city China

ISBN: (纸本)9781424450893

In this paper,we use both wavelet transform and BP neural network to identify SEMG from human upper arm. In the experiments,we decompose a single action into different parts to realize the multi-level identification of a single action. We use two electrodes to extract SEMG signal from the upper arm biceps,triceps firstly,then analyze this signal using wavelet transform and extract eight values forming the feature vector,finally put this feature vectors into BP neural network to complete pattern recognition. the results of the experiments using the method introduced in this paper show that the average recognition rate of arm internal rotating, external rotating, arm stretching, 1 / 3 bending, 1 / 2 bending and full bending is over 90%. © 2011 IEEE.

关键词： Wavelet transforms

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Identify and classify pulse information based on extension

Identify and classify pulse information based on extension

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5th IEEE international conference on Industrial Informatics

作者： Zhu, Xiaoyuan Yu, Yongquan Li, Zhilong Wang, Hong Guang Dong Univ Technol Fac Comp Dept Guangzhou 510090 Peoples R China

ISBN: (纸本)9781424408504

Human pulse always has tiny change. the veracity of pulse diagnosis affects individual life. the paper presents using the extension method and establishing the matter-element model for identifying pulse information. It constructs the extension classify-instrument with the extension classification tree. According to the experiment results, the method is compared with other current recognition methods. Research results indicate that it is of great help to identify and classify pulse information by constructing extension classify-instrument.

关键词： bioinformatics

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Age Invariant Face recognition using Frangi2D Binary pattern 19

Age Invariant Face Recognition using Frangi2D Binary Pattern

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2nd international conference on Image and Graphics Processing (ICIGP) / 5th international conference on Virtual Reality

作者： Afroze, Sabah Beham, M. Parisa Tamilselvi, R. Maraikkayar, S. M. Seeni Mohamed Aliar Rajakumar, K. Sethu Inst Technol Dept Elect & Commun Engn Pulloor 626115 Tamil Nadu India

ISBN: (纸本)9781450360920

the field of computer vision is devoted to discovering algorithms, data representations and computer architectures that embody the principles underlying visual capabilities. Computer vision is an interdisciplinary field that deals with how computers can be made for gaining high level understanding from digital images or videos. While very promising result has been shown on face recognition related problems, age invariant face recognition still relics a challenge. Facial appearance of a human varies over time, which results in substantial intra-class variations. In order to address this problem, we propose Frangi2D method for normalization, Linear Binary pattern (LBP) for feature extraction and Sparse Representation Classifier (SRC). Extensive results on a well-known public domain face aging dataset: MORPH. the experimental results show the superiority of our proposed method in age invariant face recognition.

关键词： Age Invariant Face recognition Frangi 2D sparse representation classifier (SRC) Local binary pattern (LBP)

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Self-formation supported by pattern recognition

Self-formation supported by pattern recognition

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6th international conference on Self-Formation theory and Applications

作者： Telksnys, L Inst Math & Informat Recognit Proc Dept LT-2600 Vilnius Lithuania

Artificial planar systems self-formation process supported by pattern recognition theory and methods are discussed. Concept possibilities to apply pattern recognition power for improving and control self-formation pro... 详细信息

ISBN: (纸本)3908450853

关键词： self-formation pattern recognition

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Automated Rehabilitation Exercise Assessment by Genetic Algorithm-optimized CNN 10

Automated Rehabilitation Exercise Assessment by Genetic Algo...

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Joint 10th international conference on Informatics, Electronics and Vision, ICIEV 2021 and 2021 5th international conference on Imaging, Vision and pattern recognition, icIVPR 2021

作者： Raihan, Md Johir Ahad, Md Atiqur Rahman Nahid, Abdullah-Al Electronics and Communication Engineering Discipline Khulna University Khulna9208 Bangladesh Dept. of Electrical and Electronic Engineering University of Dhaka Dhaka Bangladesh

ISBN: (纸本)9781665449212

Every year, the number of motor dysfunction patients has been rising. these patients require physical therapy and continuous observation and assessment of their exercises by a professional therapist. this process can take a longer time, leading to a staff shortage and increasing financial costs. thus, a reliable rehabilitation framework is necessary to assess these exercises as precisely as possible. In this paper, we have proposed an exercise assessment framework using the 1D Local Binary pattern (LBP) to extract valuable features from skeleton data and a genetic algorithm (GA) optimized Convolutional Neural Network (CNN) to predict the score. the KIMORE dataset has been used in this study. We have achieved 0.0165 Mean Absolute Deviation (MAD) on the training set and 0. 13515 on the validation set. Contribution- We have proposed a rehabilitation exercise assessment framework based on 1D Local Binary pattern (LBP) and Genetic Algorithm (GA) optimized CNN. © 2021 IEEE

关键词： Local binary pattern

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Design and Implementation of a Robust System for Recognizing Alphabets using Artifical Neural Network 5

Design and Implementation of a Robust System for Recognizing...

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5th international conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO)

作者： Kapoor, Shubhankar Singh, Ashish Goswami, Utkarsh Kumar, Saswat Chitranshi, Gaurav Amity Univ Dept Elect & Commun Engn Noida Uttar Pradesh India

ISBN: (纸本)9781509014897

Language or pattern recognition is an ever-growing field in research. the motivation behind this work is the growing importance of foreign languages in everyday life. It is specifically focused on groups who might have to face a foreign language somewhere and can't seem to understand it. this will also be beneficial for partially visually impaired persons. It will help in recognizing the alphabets and letters written in a particular language stored in the database. the program was trained with different samples of a different letters of an alphabet and the data was stored. Using Artificial Neural Network and pattern recognition techniques, the hardware can now read whatever form of letter is presented in front of it. Using the neural network the success rate was found to be higher than 97%.

关键词： Artificial neural network supervised learning pattern recognition

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Frequent Episode Mining to Support pattern Analysis in Developmental Biology

引用

5th international conference on pattern recognition in bioinformatics

作者： Bathoorn, Ronnie Welten, Monique Richardson, Michael Siebes, Arno Verbeek, Fons J. Univ Utrecht Distributed Databases Comp Sci Utrecht Netherlands Leiden Univ Imaging & Bioinformat LIACS Leiden Netherlands

ISBN: (纸本)9783642160004

We introduce a new method for the analysis of heterochrony in developmental biology. Our method is based on methods used in data mining and intelligent data analysis and applied in, e.g., shopping basket analysis, alarm network analysis and click stream analysis. We have transferred, so called, frequent episode mining to operate in the analysis of developmental timing of different (model) species. this is accomplished by extracting small temporal patterns, i.e. episodes, and subsequently comparing the species based on extracted patterns. the method allows relating the development of different species based on different types of data. In examples we show that the method can reconstruct a phylogenetic tree based on gene-expression data as well as using strict morphological characters. the method can deal with incomplete and/or missing data. Moreover, the method is flexible and not restricted to one particular type of data: i.e., our method allows comparison of species and genes as well as morphological characters based on developmental patterns by simply transposing the dataset accordingly. We illustrate a range of applications.

关键词： frequent episode mining heterochrony pattern analysis developmental biology

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the Discrete Lifting Shapelet Transform for Biological pattern recognition

The Discrete Lifting Shapelet Transform for Biological Patte...

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5th international IEEE Engineering-in-Medicine-and-Biology-Society (EMBS) conference on Neural Engineering (NER)

作者： Pinzon-Morales, Ruben-Dario Orozco-Gutierrez, Alvaro-Angel Castellanos, Cesar-German Guido, Rodrigo Capobianco Technol Univ Pereira Pereira Colombia Univ Nacl Colombia Manizales Colombia Univ Sao Paulo Dept Phys Informat Sao Paulo Brazil

ISBN: (纸本)9781424441419

Wavelet transform has been widely used in biological signal processing since last decade. the success in the wavelet results relies on the proper selection of the mother wavelet function. In this document the wavelet function is customized to the application. Mentioned approach is possible by means of the Discrete Lifting Shapelet Transform (DLST), a novel transform introduced here and use to generate mother wavelets that resemble the shape of a match pattern and the time-frequency information within. the DLST is inspired on two works: the Discrete Shapelet Transform and the Signal-Dependent Filter Banks. Comparison results are given ensuring the efficacy of the proposed transform in the framework of hand movement recognition using electromyographic signals.

关键词： Discrete wavelet transforms Electromyography Fractals Frequency response Optimization biological pattern recognition biological signal processing biomechanics channel bank filters discrete lifting shapelet transform discrete shapelet transform electromyographic signals electromyography hand movement recognition match pattern medical signal processing mother wavelet function pattern recognition signal-dependent filter banks time-frequency analysis time-frequency information wavelet transform wavelet transforms

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LEARNING ACTION pattern FOR ACTIVITY recognition 5

LEARNING ACTION PATTERN FOR ACTIVITY RECOGNITION

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5th international conference on Enterprise Systems (ES) - Industrial Digitalization by Enterprise Systems

作者： Feng, Jingyi Ming, Anlong Yao, Chao Zhou, Yu Beijing Univ Posts & Telecommun Sch Comp Sci Beijing Peoples R China

ISBN: (纸本)9781538609361

this paper studies the challenging activity recognition task and a novel discriminative action pattern is proposed. We construct action cube pool and propose a novel scheme to represent action cubes as action patterns. Candidates of discriminative patterns are selected among action patterns according to motion energy of corresponding action cube. Spatial constraint clustering algorithm clusters these candidates into several disjoint clusters. Discriminative patterns are learned with the help of negative patterns and multi-class SVM. the presented approach is validated on the MSRAction3D dataset and the MSRDailyActivity3D dataset. the experimental results prove the effectiveness of our approach.

关键词： Action patterns action cubes activity recognition spatial constraint clustering

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Face recognition system based on novel Peak Response-based Sobel Directional pattern (PRSDP) and the Stacked Restricted Boltzmann Machine (SRBM) 5

Face recognition system based on novel Peak Response-based S...

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5th international conference on Innovative Trends in Information Technology (ICITIIT)

作者： Riyaas, Mohamed R. Alphonse, Sherly A. Vellore Inst Technol Sch Comp Sci & Engn Chennai India

ISBN: (数字)9798350386813

ISBN: (纸本)9798350386813;9798350386820

Face recognition systems are now extensively used in a variety of daily needs. Despite significant advances, occlusions, changes in light, camera types, and resolutions continue to pose challenges to face recognition systems. An effective face recognition system based on a Peak Response-based Sobel Directional pattern (PRSDP) and the Stacked Restricted Boltzmann Machine (SRBM) technique was developed in this study. the major goal of the proposed system is the improved feature extraction approach to improve the features recovered by the PRSDP by removing noise. the Principal Component Analysis and Linear Discriminant Analysis (PCA + LDA) technique is then used to decrease the enhanced features. Experiments on JAFFE, LFW and Oulu-CASIA reveal that the suggested approach, when combined with Gabor and SRBM, can generate promising results and surpass previously proposed methods.

关键词： Sobel noise face recognition image

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