Context-based Classification: With Applications in Landmine Detection

 
9783846583234: Context-based Classification: With Applications in Landmine Detection

In many applications including health-care, finance and object recognition, data classification may be hindered by the existence of multiple contexts that produce an input sample. These contexts are generally hard to define, they are often interlaced and do not have sharp boundaries. Context-based classifiers offer the promise of increasing performance by allowing classifiers to become experts at classifying input samples of certain types. In this book, we introduce several models that can simultaneously learn the contexts as well as the classifiers for static, sequential and time-series data. We demonstrate the results on landmine detection from ground penetrating radar and electro-magnetic induction sensors, and show how choosing an appropriate context can simplify the classification problems.

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About the Author:

Seniha Esen Yuksel is a postdoctoral associate at the MSE Department, University of Florida. She received her Ph.D. degree in Computer Engineering from the University of Florida, her M.Sc. degree in Electrical and Computer Engineering from the University of Louisville, USA, and her B.Sc. degree from the Middle East Technical University in Turkey.

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Book Description Book Condition: New. Publisher/Verlag: LAP Lambert Academic Publishing | With Applications in Landmine Detection | In many applications including health-care, finance and object recognition, data classification may be hindered by the existence of multiple contexts that produce an input sample. These contexts are generally hard to define, they are often interlaced and do not have sharp boundaries. Context-based classifiers offer the promise of increasing performance by allowing classifiers to become experts at classifying input samples of certain types. In this book, we introduce several models that can simultaneously learn the contexts as well as the classifiers for static, sequential and time-series data. We demonstrate the results on landmine detection from ground penetrating radar and electro-magnetic induction sensors, and show how choosing an appropriate context can simplify the classification problems. | Format: Paperback | Language/Sprache: english | 112 pp. Bookseller Inventory # K9783846583234

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Book Description LAP Lambert Academic Publishing Mrz 2012, 2012. Taschenbuch. Book Condition: Neu. Neuware - In many applications including health-care, finance and object recognition, data classification may be hindered by the existence of multiple contexts that produce an input sample. These contexts are generally hard to define, they are often interlaced and do not have sharp boundaries. Context-based classifiers offer the promise of increasing performance by allowing classifiers to become experts at classifying input samples of certain types. In this book, we introduce several models that can simultaneously learn the contexts as well as the classifiers for static, sequential and time-series data. We demonstrate the results on landmine detection from ground penetrating radar and electro-magnetic induction sensors, and show how choosing an appropriate context can simplify the classification problems. 112 pp. Englisch. Bookseller Inventory # 9783846583234

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Book Description LAP Lambert Academic Publishing Mrz 2012, 2012. Taschenbuch. Book Condition: Neu. Neuware - In many applications including health-care, finance and object recognition, data classification may be hindered by the existence of multiple contexts that produce an input sample. These contexts are generally hard to define, they are often interlaced and do not have sharp boundaries. Context-based classifiers offer the promise of increasing performance by allowing classifiers to become experts at classifying input samples of certain types. In this book, we introduce several models that can simultaneously learn the contexts as well as the classifiers for static, sequential and time-series data. We demonstrate the results on landmine detection from ground penetrating radar and electro-magnetic induction sensors, and show how choosing an appropriate context can simplify the classification problems. 112 pp. Englisch. Bookseller Inventory # 9783846583234

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Book Description LAP Lambert Academic Publishing, Germany, 2012. Paperback. Book Condition: New. Aufl.. Language: English . Brand New Book. In many applications including health-care, finance and object recognition, data classification may be hindered by the existence of multiple contexts that produce an input sample. These contexts are generally hard to define, they are often interlaced and do not have sharp boundaries. Context-based classifiers offer the promise of increasing performance by allowing classifiers to become experts at classifying input samples of certain types. In this book, we introduce several models that can simultaneously learn the contexts as well as the classifiers for static, sequential and time-series data. We demonstrate the results on landmine detection from ground penetrating radar and electro-magnetic induction sensors, and show how choosing an appropriate context can simplify the classification problems. Bookseller Inventory # KNV9783846583234

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Book Description LAP Lambert Academic Publishing. Paperback. Book Condition: New. Paperback. 112 pages. Dimensions: 8.7in. x 5.9in. x 0.3in.In many applications including health-care, finance and object recognition, data classification may be hindered by the existence of multiple contexts that produce an input sample. These contexts are generally hard to define, they are often interlaced and do not have sharp boundaries. Context-based classifiers offer the promise of increasing performance by allowing classifiers to become experts at classifying input samples of certain types. In this book, we introduce several models that can simultaneously learn the contexts as well as the classifiers for static, sequential and time-series data. We demonstrate the results on landmine detection from ground penetrating radar and electro-magnetic induction sensors, and show how choosing an appropriate context can simplify the classification problems. This item ships from multiple locations. Your book may arrive from Roseburg,OR, La Vergne,TN. Paperback. Bookseller Inventory # 9783846583234

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