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Keywords
(7)
Feed Forward Neural Network
Pattern Recognition
Probability Density Function
Radial Basis Function Network
Statistical Pattern Recognition
Multi Layer Perceptron
Neural Network
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Neural Networks for Pattern Recognition
Neural Networks for Pattern Recognition,Christopher M. Bishop
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Neural Networks for Pattern Recognition
(
Citations: 9324
)
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Christopher M. Bishop
his is the first comprehensive treatment of feedforward neural networks from the perspective of statistical pattern recognition. After introducing the basic concepts, the book examines techniques for modelling
probability density
functions and the properties and merits of the multilayer perceptron and
radial basis function network
models. Also covered are various forms of error functions, principal algorithms for error function minimalization, learning and generalization in neural networks, and Bayesian techniques and their applications. Designed as a text, with over 100 exercises, this fully uptodate work will benefit anyone involved in the fields of neural computation and pattern recognition.
Published in 1995.
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Annual
Citation Context
(5002)
...Numerous developments in neural networks have demonstrated that they are good at pattern recognition [
2
, 22]...
Jingpeng Li
,
et al.
A pattern recognition based intelligent search method and two assignme...
...The keyideaistomodelthescoredensityconditionedontheclass variable k. Modeling class conditional density is the fundamental building block in constructing a Bayes classifier [
38
]...
...In particular, when pðqjQÞ is Gaussian, it is known as Gaussian Mixture Model (GMM) [
38
]...
...The second model, P ðCjy; qÞ, can be directly approximated using logistic regression or a multilayer Perceptron with a sigmoid activation function [
38
]...
...In the machinelearning literature [
38
], this is known as the mixture of experts and P ðQjqÞ is known as a gater, which plays the role of assigning the most competent expert to a subspace of the problem...
...This is because, consistent with the literature on machine learning [
38
], the discriminative approach requires much fewer parameters to estimate than the generative one, making the former much more suited to a large number of quality measures of which not all may be relevant...
...Consistent with the machinelearning literature [
38
], correlation among quality measures, if present, will be automatically taken into consideration...
Norman Poh
,
et al.
A Unified Framework for Biometric Expert Fusion Incorporating Quality ...
...However, one of the reported strengths of a neural network is its ability to perform well on datasets that is not part of the training dataset (Bishop
1995
)...
Amin Tayyebi
,
et al.
Hierarchical modeling of urban growth across the conterminous USA: dev...
...In particular, the variables that describe which hidden units could have caused a spike in a translationinvariant neuron are not mutually exclusive, whereas the EM algorithm for mixture models (Bishop,
2004
) operates with probabilities of hidden variables that are, although not directly observable, can take only one value at a time with some probability...
Michael Eickenberg
,
et al.
Characterizing Responses of TranslationInvariant Neurons to Natural S...
...This basically involves solving a quadratic programming problem, while gradient based training methods for neural network architectures on the other hand suffer from the existence of many local minima (Bishop
1995
), (Cherkassky and Mulier
2007
), (Fletcher
2000
)...
Werickson F. C. Rocha
,
et al.
Chemometric Techniques Applied for Classification and Quantification o...
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Citations
(9324)
A pattern recognition based intelligent search method and two assignment problem case studies
(
Citations: 1
)
Jingpeng Li
,
Edmund K. Burke
,
Rong Qu
Published in 2012.
Crashworthiness optimisation of vehicle structures with magnesium alloy parts
(
Citations: 1
)
Andrew Parrish
,
Masoud RaisRohani
,
Ali Najafi
Journal:
International Journal of Crashworthiness  INT J CRASHWORTHINESS
, vol. aheadofp, no. aheadofp, pp. 123, 2012
A Unified Framework for Biometric Expert Fusion Incorporating Quality Measures
Norman Poh
,
Josef Kittler
Journal:
IEEE Transactions on Pattern Analysis and Machine Intelligence  PAMI
, vol. 34, no. 1, pp. 318, 2012
Hierarchical modeling of urban growth across the conterminous USA: developing mesoscale quantity drivers for the Land Transformation Model
Amin Tayyebi
,
Burak K. Pekin
,
Bryan C. Pijanowski
,
James D. Plourde
,
Jarrod S. Doucette
,
David Braun
Journal:
Journal of Land Use Science
, vol. aheadofp, no. aheadofp, pp. 121, 2012
Characterizing Responses of TranslationInvariant Neurons to Natural Stimuli: Maximally Informative Invariant Dimensions
Michael Eickenberg
,
Ryan J. Rowekamp
,
Minjoon Kouh
,
Tatyana O. Sharpee
Journal:
Neural Computation  NECO
, vol. 24, no. 9, pp. 23842421, 2012