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Local Context Finder (LCF) reveals multidimensional relationships among mRNA expression profiles of Arabidopsis responding to pathogen infection
2003
Proceedings of the National Academy of Sciences of the United States of America
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A pattern recognition method called Local Context Finder (LCF) is described here. LCF uses nonlinear dimensionality reduction for pattern recognition. ...
This is generally achieved by pattern recognition in the distribution of data points representing each profile in a high-dimensional space. ...
(7) and Roweis and Saul (8) developed two different algorithms, Isomap and Locally Linear Embedding (LLE), respectively, to perform nonlinear dimensionality reduction for the purpose of pattern recognition ...
doi:10.1073/pnas.1934349100
pmid:12960373
pmcid:PMC196890
fatcat:ikhzdue57naxram6z5o2tnb3au
Dimensionality Reduction Oriented Toward the Feature Visualization for Ischemia Detection
2009
IEEE Transactions on Information Technology in Biomedicine
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set is projected to a 2-D space in order to verify the performance of the suggested dimension reduction algorithm in terms of the discrimination capability for ischemia detection. ...
Next, an algorithm of variable selection is provided that further reduces the dimension, taking into account only the variables that offer greater class separability, and finally, the selected feature ...
It can be noted that the observations for each one of the classes have a geometric disposition that makes pattern separability difficult. ...
doi:10.1109/titb.2009.2016654
pmid:19304491
fatcat:3w2br4rjrbhrxdxdvk2coypvqi
Measuring group-separability in geometrical space for evaluation of pattern recognition and embedding algorithms
[article]
2019
arXiv
pre-print
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Evaluating data separation in a geometrical space is fundamental for pattern recognition. ...
A plethora of dimensionality reduction (DR) algorithms have been developed in order to reveal the emergence of geometrical patterns in a low dimensional visible representation space, in which high-dimensional ...
Group separability aims to evaluate in a geometrical space the extent to which groups (classes or populations) that are partially overlapping [21] , [22] , and display a pattern of separation between ...
arXiv:1912.12418v1
fatcat:wpcivrwpsjhcfnir36bidvvnk4
Dimensionality Reduction by Locally Linear Discriminant Analysis for Handwritten Chinese Character Recognition
2012
IEICE transactions on information and systems
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Linear Discriminant Analysis (LDA) is one of the most popular dimensionality reduction techniques in existing handwritten Chinese character (HCC) recognition systems. ...
A series of experiments on both the HCL2000 and CASIA Chinese character handwriting databases show that our method can effectively improve recognition performance, with a reduction in error rate of 28.7% ...
Acknowledgments This work is supported in part by NSFC (no. U0735004, 60772116, 61075021, 60902087) and GDSFC (no. S2011020000541, 2010B090400397, 2011B090400146). ...
doi:10.1587/transinf.e95.d.2533
fatcat:mhlqmcafpzbzndrvpfb3whlg2i
Review of Printed Fabric Pattern Segmentation Analysis and Application
2019
Autex Research Journal
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Several robust and efficient segmentation algorithms are established for pattern recognition. ...
Image processing of digital images is one of the essential categories of image transformation in the theory and practice of digital pattern analysis and computer vision. ...
Acknowledgments This work was financially supported by the Fundamental Research Funds for the Central Universities (JUSRP 41804). ...
doi:10.2478/aut-2019-0049
fatcat:4mvncw7jqraqnn2ff5ynjawd5a
Binary Large Object-Based Approach for QR Code Detection in Uncontrolled Environments
2017
Journal of Electrical and Computer Engineering
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The proposal consists in recognizing geometrical features of QR code using a binary large object- (BLOB-) based algorithm with subsequent iterative filtering QR symbol position detection patterns that ...
The main disadvantage of recent applications for QR code detection is a low performance for rotated and distorted single or multiple symbols in images with variable illumination and presence of noise. ...
of multiple simple geometric shapes over a fixed space. ...
doi:10.1155/2017/4613628
fatcat:un4j6pneoncizokob32s4mrhc4
Machine Learning Approaches: From Theory to Application in Schizophrenia
2013
Computational and Mathematical Methods in Medicine
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First we give a description of the basic terminology used in pattern recognition and machine learning. ...
In particular, we focus on the algorithms implemented by our group, which have been applied to classify subjects affected by schizophrenia and healthy controls, comparing them in terms of accuracy results ...
Acknowledgments This study was partially supported by grants from the Italian Ministry of Health to Dr. Paolo Brambilla (GR-2010-2316745) and to Dr. Marcella Bellani (GR-2010-2319022). ...
doi:10.1155/2013/867924
pmid:24489603
pmcid:PMC3893837
fatcat:mhjhzq6ly5c2poqh6thznr7dyi
Feature Extraction Trends for Intelligent Facial Expression Recognition: A Survey
2018
Informatica (Ljubljana, Tiskana izd.)
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Face detection, feature extraction and expression classification are the three main stages in the process of Facial Expression Recognition (FER). ...
In human-machine interaction facial expression recognition plays a vital role. Still facial expression recognition through machines like computer is a difficult task. ...
rate
higher than 97%
• Dimension reduction,
• Similar recognition
performance obtained
in both using YUV
color space and RGB
color space
• ROI extraction is
accurate even if the
brightness changes ...
doi:10.31449/inf.v42i4.2037
fatcat:zcmaj5oesneklfhf3ask7qbxsa
Computational intelligence techniques to detect toxic gas presence
2006
2006 IEEE International Conference on Computational Intelligence for Measurement Systems and Applications
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The aim of this paper is to critically discuss the use of a-priori knowledge in the design of gas sensor systems implementing computational intelligence techniques for signal processing and gas presence ...
The availability of a-priori information about the probability density function of the considered classes as well as about the class separation boundary (Bayes boundary) allow the classifier designer for ...
Dario Narducci and Ing. Dario Cogliati. The present activity has been supported by Fondazione Cariplo, Italy, under project TARGET. ...
doi:10.1109/cimsa.2006.250745
fatcat:gtvgx7pfi5eafpgissybacfg5y
An OD Flow Clustering Method Based on Vector Constraints: A Case Study for Beijing Taxi Origin-Destination Data
2020
ISPRS International Journal of Geo-Information
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of high-dimensional similarity of OD flow and helps mining representative OD flow clusters in flow space. ...
Origin-destination (OD) flow pattern mining is an important research method of urban dynamics, in which OD flow clustering analysis discovers the activity patterns of urban residents and mine the coupling ...
Acknowledgments: The authors would like to thank the anonymous reviewers for their valuable comments.
Conflicts of Interest: The authors declare no conflict of interest. ...
doi:10.3390/ijgi9020128
fatcat:jhoo32ndxzewtnfo6dc3lt54om
Kernel Locality Preserving Symmetrical Weighted Fisher Discriminant Analysis based subspace approach for expression recognition
2016
Engineering Science and Technology, an International Journal
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This paper mainly focuses on dimensional reduction of fused dataset of holistic and geometrical face features vectors by solving singularity problem of linear discriminant analysis and maximizing the Fisher ...
Performance of proposed approach is evaluated and compared with state of art approaches. ...
The ''kernel trick" [58] allows for the computation of algorithms in a kernel domain space without explicitly evaluating the mapping, as long as the algorithm can be expressed in terms of dot products ...
doi:10.1016/j.jestch.2016.03.005
fatcat:hpt3nlyxqrhbhmblmdzakiw5hm
Learning Non-Euclidean Representations with SPD Manifold for Myoelectric Pattern Recognition
2022
IEEE transactions on neural systems and rehabilitation engineering
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It shows the effectiveness of the presented approach and contributes a new way for myoelectric pattern recognition. ...
Traditionally, hand-crafted features are extracted from individual EMG channels and combined together for pattern recognition. ...
After that, a tangent feature matrix is flattened and dimension reduced for pattern recognition. ...
doi:10.1109/tnsre.2022.3178384
pmid:35622796
fatcat:lsi2fiuaabdwligqe2ygo5nx6u
Performance study of dimensionality reduction methods for metrology of nonrigid mechanical parts
2013
International Journal of Metrology and Quality Engineering
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In this paper we will only present a systematic comparison of some well-known dimensionality reduction techniques in order to evaluate their accuracy and potential for non-rigid metrology. ...
The geometric measurement of parts using a coordinate measuring machine (CMM) has been generally adapted to the advanced automotive and aerospace industries. ...
Acknowledgements
This research is partially supported by the National Sciences and Engineering Research Council (NSERC). We also appreciate the authors of different codes in NLDR methods. ...
doi:10.1051/ijmqe/2013051
fatcat:t4sej52dfbehddofyidlsuvkzi
Manifold Learning Algorithms Applied to Structural Damage Classification
2021
Journal of Applied and Computational Mechanics
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Results evaluated in an experimental setup showed that the best classification accuracy was 100% when the methodology uses isomap algorithm with a hyperparameter k of 170 and 8 dimensions as a feature ...
A comparative study of four manifold learning algorithms was carried out to perform the dimensionality reduction process within a proposed methodology for damage classification in structural health monitoring ...
The authors thank the Editor and the anonymous reviewers for their valuable comments and suggestions. ...
doi:10.22055/jacm.2020.33055.2139
doaj:c64a31504016409aa055c55c131b3a48
fatcat:s6j53rcy6ra5znrrfwy7n6xsuu
Appearance-based object recognition using optimal feature transforms
2000
Pattern Recognition
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We summarize several methods for improving the recognition rates and pose estimation accuracy of existing algorithms for 3 D object recognition. ...
the feature dimensions and to beat the curse of dimensionality. ...
Murase and K. Nayar for the friendly admission to use their Software Library for Appearance Matching SLAM. ...
doi:10.1016/s0031-3203(99)00048-5
fatcat:n7pmltkysfgsbdz7ur4y642shy
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