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https://patents.google.com/patent/US5649068A/en
US5649068A US08/648,641 US64864196A US5649068A US 5649068 A US5649068 A US 5649068A US 64864196 A US64864196 A US 64864196A US 5649068 A US5649068 A …Cited by: 194
https://www.di.ens.fr/~mallat/papiers/svmtutorial.pdf
A Tutorial on Support Vector Machines for Pattern Recognition CHRISTOPHER J.C. BURGES [email protected] Bell Laboratories, Lucent Technologies ... some recent applications and extensions of support vector machines. For the pattern recog-nition case, SVMs have been used for isolated handwritten digit recognition (Cortes and ... of vectors and ...
http://people.csail.mit.edu/dsontag/courses/ml12/notes/burges_SVM_tutorial.pdf
A Tutorial on Support Vector Machines for Pattern Recognition CHRISTOPHER J.C. BURGES [email protected] Bell Laboratories, Lucent Technologies Abstract. The tutorial starts with an overview of the concepts of VC dimension and structural risk minimization. We then describe linear Support Vector Machines (SVMs) for separable and non-separable
https://arxiv.org/pdf/1605.06742.pdf
A Rapid Pattern-Recognition Method for Driving Styles Using Clustering-Based Support Vector Machines Wenshuo Wang1 and Junqiang Xi2 Abstract—A rapid pattern-recognition approach to char-acterize driver’s curve-negotiating behavior is proposed. To shorten the recognition time and improve the recognition of
https://pdfs.semanticscholar.org/ea7e/998a5cf55a62ba744a18e69734ee2e541cf3.pdf
Support Vector Machines [1-4] is a learning technique that can be viewed as a new method for training polynomial, neural network, or Radial Basis Functions Classifiers. The decision surfaces are found by solving a linearly constrained quadratic programming problem. This paper evaluates the use of Support Vector Machines for object recognition.
http://www.enggjournals.com/ijet/docs/IJET17-09-03S-008.pdf
Support Vector Machine (SVM) is a classification technique developed by Cortes & Vapnik, originally designed for binary classification. While traditional methods of pattern recognition try to minimize the empirical risk, SVM tries to minimize structural risk.
https://www.worldscientific.com/doi/abs/10.1142/S0218001410007865
Change Point Detection in time series data is of interest in various research areas including data mining, pattern recognition, statistics, etc. Even though there are several effective methods in the literature for detecting changes in mean, and an increase in variance, there are none for decrease in variance.Cited by: 8
https://ieeexplore.ieee.org/document/5697461/
Dec 17, 2010 · Palm print recognition using Local Binary Pattern operator and support vector machines ... With the feature vectors so obtained we perform matching using Support vector machines (SVM) and also using the Chi-square distance measurement. The experimental results presented in this paper show significant improvement in the performance of the ...
https://www.researchgate.net/publication/2427763_Face_Recognition_by_Support_Vector_Machines
Support Vector Machines (SVMs) have been recently proposed as a new technique for pattern recognition. In this paper, the SVMs with a binary tree recognition strategy are used to tackle the face ...
https://www.vision-systems.com/home/article/16737424/support-vector-machines-speed-pattern-recognition
Support vector machines speed pattern recognition. Numerous image-processing and machine-vision libraries are available that use search algorithms. Despite this, many of these software packages cannot recognize objects that are, by nature, subject to deformation or naturally occurring variations.
https://arxiv.org/pdf/1605.06742.pdf
A Rapid Pattern-Recognition Method for Driving Styles Using Clustering-Based Support Vector Machines Wenshuo Wang1 and Junqiang Xi2 Abstract—A rapid pattern-recognition approach to char-acterize driver’s curve-negotiating behavior is proposed. To shorten the …
https://www.slideshare.net/AlexanderDecker/pattern-recognition-system-based-on-support-vector-machines
Sep 01, 2013 · Pattern recognition system based on support vector machines 1. Control Theory and Informatics www.iiste.org ISSN 2224-5774 (Paper) ISSN 2225-0492 (Online) Vol.3, No.3, 2013 1 Pattern recognition system based on support vector machines: HIV-1 integrase inhibitors application Rachid Darnag1* Brahim Minaoui2 Mohamed Fakir3 1.
https://ui.adsabs.harvard.edu/abs/2016arXiv160506742W/abstract
A rapid pattern-recognition approach to characterize driver's curve-negotiating behavior is proposed. To shorten the recognition time and improve the recognition of driving styles, a k-means clustering-based support vector machine ( kMC-SVM) method is developed and used for classifying drivers into two types: aggressive and moderate. First, vehicle speed and throttle opening are treated as the ...Cited by: 19
http://www.cs.northwestern.edu/~pardo/courses/eecs349/readings/support_vector_machines4.pdf
A Tutorial on Support Vector Machines for Pattern Recognition CHRISTOPHER J.C. BURGES [email protected] Bell Laboratories, Lucent Technologies Editor: Usama Fayyad Abstract. The tutorial starts with an overview of the concepts of VC dimension and structural risk minimization. We then describe linear Support Vector Machines (SVMs) for separable ...
https://papers.nips.cc/paper/1609-support-vector-machines-applied-to-face-recognition.pdf
Support Vector Machines Applied to Face Recognition 805 SVM can be extended to nonlinear decision surfaces by using a kernel K ( " .) that satisfies Mercer's condition [1, 7]. The nonlinear decision surface is L Ns oWiK(sj, z) + b = O. i= l A facial image is represented as a vector P …
http://cbcl.mit.edu/publications/ps/iccv2001.pdf
Face Recognition with Support Vector Machines: Global versus Component-based Approach Bernd Heisele Purdy Ho Tomaso Poggio Massachusetts Institute of Technology Center for Biological and Computational Learning Cambridge, MA 02142 [email protected] [email protected] [email protected] Abstract We present a component-based method and two global methods ...
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