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Applied Graph Theory in Computer Vision and Pattern Recognition

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Cover of 'Applied Graph Theory in Computer Vision and Pattern Recognition'

Table of Contents

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    Book Overview
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    Chapter 1 Multiresolution Image Segmentations in Graph Pyramids
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    Chapter 2 A Graphical Model Framework for Image Segmentation
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    Chapter 3 Digital Topologies on Graphs
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    Chapter 4 How and Why Pattern Recognition and Computer Vision Applications Use Graphs
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    Chapter 5 Efficient Algorithms on Trees and Graphs with Unique Node Labels
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    Chapter 6 A Generic Graph Distance Measure Based on Multivalent Matchings
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    Chapter 7 Learning from Supervised Graphs
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    Chapter 8 Graph-Based and Structural Methods for Fingerprint Classification
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    Chapter 9 Graph Sequence Visualisation and its Application to Computer Network Monitoring and Abnormal Event Detection
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    Chapter 10 Clustering of Web Documents Using Graph Representations
Attention for Chapter 7: Learning from Supervised Graphs
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