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From Global to Local Statistical Shape Priors - Novel Methods to Obtain Accurate Reconstruction Results with a Limited Amount of Training Shapes (Hardcover, 1st ed. 2017) Loot Price: R3,384
Discovery Miles 33 840
Repayment Terms: R317 pm x 12*
You Save: R261 (7%)
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From Global to Local Statistical Shape Priors - Novel Methods to Obtain Accurate Reconstruction Results with a Limited Amount...

From Global to Local Statistical Shape Priors - Novel Methods to Obtain Accurate Reconstruction Results with a Limited Amount of Training Shapes (Hardcover, 1st ed. 2017)

Carsten Last

Series: Studies in Systems, Decision and Control, 98

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List price R3,645 Loot Price R3,384 Discovery Miles 33 840 | Repayment Terms: R317 pm x 12* You Save R261 (7%)

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This book proposes a new approach to handle the problem of limited training data. Common approaches to cope with this problem are to model the shape variability independently across predefined segments or to allow artificial shape variations that cannot be explained through the training data, both of which have their drawbacks. The approach presented uses a local shape prior in each element of the underlying data domain and couples all local shape priors via smoothness constraints. The book provides a sound mathematical foundation in order to embed this new shape prior formulation into the well-known variational image segmentation framework. The new segmentation approach so obtained allows accurate reconstruction of even complex object classes with only a few training shapes at hand.

General

Imprint: Springer International Publishing AG
Country of origin: Switzerland
Series: Studies in Systems, Decision and Control, 98
Release date: March 2017
First published: 2017
Authors: Carsten Last
Dimensions: 235 x 155 x 18mm (L x W x T)
Format: Hardcover
Pages: 259
Edition: 1st ed. 2017
ISBN-13: 978-3-319-53507-4
Categories: Books > Science & Mathematics > Mathematics > Applied mathematics > General
Books > Computing & IT > Applications of computing > Artificial intelligence > Computer vision
Books > Professional & Technical > Electronics & communications engineering > Electronics engineering > Automatic control engineering > Robotics
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LSN: 3-319-53507-2
Barcode: 9783319535074

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