Chapter: Competitive Neural Networks for Image Segmentation

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Home > Neural Networks: Computational Models and Applications > Competitive Neural Networks for Image Segmentation

Neural Networks: Computational Models and Applications |

Huajin Tang; Kay Chen Tan; Zhang Yi

Springer Berlin Heidelberg

Neural Networks: Computational Models and Applications

Competitive Neural Networks for Image Segmentation

Chapter Info

ARI Id

1664340743095_1285609

Access

Not Available Free

Pages

129-144

DOI

10.1007/978-3-540-69226-3_9

Chapter URL

https://rd.springer.com/chapter/10.1007/978-3-540-69226-3_9

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Chapters/Headings	Author(s)	Pages	Info
Front Matter		I-XXII
Introduction		1-7
Feedforward Neural Networks and Training Methods		9-21
New Dynamical Optimal Learning for Linear Multilayer FNN		23-34
Fundamentals of Dynamic Systems		35-56
Various Computational Models and Applications		57-79
Convergence Analysis of Discrete Time RNNs for Linear Variational Inequality Problem		81-97
Parameter Settings of Hopfield Networks Applied to Traveling Salesman Problems		99-116
Competitive Model for Combinatorial Optimization Problems		117-128
Competitive Neural Networks for Image Segmentation		129-144
Columnar Competitive Model for Solving Multi-Traveling Salesman Problem		145-160
Improving Local Minima of Columnar Competitive Model for TSPs		161-175
A New Algorithm for Finding the Shortest Paths Using PCNN		177-189
Qualitative Analysis for Neural Networks with LT Transfer Functions		191-209
Analysis of Cyclic Dynamics for Networks of Linear Threshold Neurons		211-234
LT Network Dynamics and Analog Associative Memory		235-257
Output Convergence Analysis for Delayed RNN with Time Varying Inputs		259-277
Background Neural Networks with Uniform Firing Rate and Background Input		279-288
Back Matter		289-299
Chapters/Headings	Author(s)	Pages	Info

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