Pattern Recognition and Image Preprocessing
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advanced neural network models for image analysis
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class
Committee Machine
computer vision systems
Data Set
Decision Surface
dekker
dimensionality reduction techniques
discriminant
Discriminant Function
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feature selection methods
Fisher's discriminant
function
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Hidden Layer
Hough Transform
image preprocessing
Input Vector
ISODATA Algorithm
Kohonen Self-organizing Feature Maps
levels
Linearly Separable
marcel
Medial Axis Transformation
MLP
neural networks
Pattern Classification
Pattern Classification System
Pattern Points
pattern recognition
Pattern Recognition System
Pattern Space
Pattern Vectors
points
Prototype Vector
Quadratic Discriminant Function
Radial Basis Function Network
RBF Network
space
statistical classification models
STFT
supervised learning algorithms
Systolic Array
Telocentric Chromosome
unsupervised clustering
vectors
wavelet transform
Product details
- ISBN 9780824706593
- Weight: 1088g
- Dimensions: 152 x 229mm
- Publication Date: 11 Jan 2002
- Publisher: Taylor & Francis Inc
- Publication City/Country: US
- Product Form: Hardback
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Describing non-parametric and parametric theoretic classification and the training of discriminant functions, this second edition includes new and expanded sections on neural networks, Fisher's discriminant, wavelet transform, and the method of principal components. It contains discussions on dimensionality reduction and feature selection, novel computer system architectures, proven algorithms for solutions to common roadblocks in data processing, computing models including the Hamming net, the Kohonen self-organizing map, and the Hopfield net, detailed appendices with data sets illustrating key concepts in the text, and more.
