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Knowledge Engineering, Machine Learning and Lattice Computing with Applications

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Cover of 'Knowledge Engineering, Machine Learning and Lattice Computing with Applications'

Table of Contents

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    Book Overview
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    Chapter 1 Investigation of Random Subspace and Random Forest Regression Models Using Data with Injected Noise
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    Chapter 2 A Genetic Algorithm vs. Local Search Methods for Solving the Orienteering Problem in Large Networks
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    Chapter 3 Dynamic Structure of Volterra-Wiener Filter for Reference Signal Cancellation in Passive Radar
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    Chapter 4 A Web Browsing Cognitive Model
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    Chapter 5 Optimization of Approximate Decision Rules Relative to Number of Misclassifications: Comparison of Greedy and Dynamic Programming Approaches
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    Chapter 6 Set-Based Detection and Isolation of Intersampled Delays and Pocket Dropouts in Networked Control
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    Chapter 7 Analysis and Synthesis of the System for Processing of Sign Language Gestures and Translatation of Mimic Subcode in Communication with Deaf People
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    Chapter 8 Prediction of Software Quality Based on Variables from the Development Process
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    Chapter 9 Mining High Performance Managers Based on the Results of Psychological Tests
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    Chapter 10 Semantics Preservation in Schema Mappings within Data Exchange Systems
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    Chapter 11 Multi-Relational Learning for Recommendation of Matches between Semantic Structures
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    Chapter 12 Semantically Enhanced Text Stemmer (SETS) for Cross-Domain Document Clustering
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    Chapter 13 Ontology Recomposition
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    Chapter 14 Structured Construction of Knowledge Repositories with MetaConcept
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    Chapter 15 Association between Teleology and Knowledge Mapping
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    Chapter 16 Boosting Retrieval of Digital Spoken Content
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    Chapter 17 Constructing the Integral OLAP-Model for Scientific Activities Based on FCA
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    Chapter 18 Reasoning about Dialogical Strategies
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    Chapter 19 Low–Cost Computer Vision Based Automatic Scoring of Shooting Targets
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    Chapter 20 Using bookmaker odds to predict the final result of football matches
Attention for Chapter 19: Low–Cost Computer Vision Based Automatic Scoring of Shooting Targets
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Chapter title
Low–Cost Computer Vision Based Automatic Scoring of Shooting Targets
Chapter number 19
Book title
Knowledge Engineering, Machine Learning and Lattice Computing with Applications
Published by
Springer, Berlin, Heidelberg, September 2012
DOI 10.1007/978-3-642-37343-5_19
Book ISBNs
978-3-64-237342-8, 978-3-64-237343-5
Authors

Jacek Rudzinski, Marcin Luckner

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 4 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 4 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 1 25%
Professor > Associate Professor 1 25%
Unknown 2 50%
Readers by discipline Count As %
Unspecified 1 25%
Computer Science 1 25%
Unknown 2 50%