Framework for Analysis and Identification of Nonlinear Distributed Parameter Systems using Bayesian Uncertainty Quantification based on Generalized Polynomial Chaos
Language: en
Pages: 248
Authors: Janya-anurak, Chettapong
Categories: Electronic computers. Computer science
Type: BOOK - Published: 2017-04-04 - Publisher: KIT Scientific Publishing

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In this work, the Uncertainty Quantification (UQ) approaches combined systematically to analyze and identify systems. The generalized Polynomial Chaos (gPC) exp
Framework for Analysis and Identification of Nonlinear Distributed Parameter Systems Using Bayesian Uncertainty Quantification Based on Generalized Polynomial Chaos
Language: en
Pages: 238
Authors: Chettapong Janya-anurak
Categories: Mathematics
Type: BOOK - Published: 2020-10-09 - Publisher:

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In this work, the Uncertainty Quantification (UQ) approaches combined systematically to analyze and identify systems. The generalized Polynomial Chaos (gPC) exp
Distributed Planning for Self-Organizing Production Systems
Language: en
Pages: 210
Authors: Pfrommer, Julius
Categories:
Type: BOOK - Published: 2024-06-04 - Publisher: KIT Scientific Publishing

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In dieser Arbeit wird ein Ansatz entwickelt, um eine automatische Anpassung des Verhaltens von Produktionsanlagen an wechselnde Aufträge und Rahmenbedingungen
Image-Based 3D Reconstruction of Dynamic Objects Using Instance-Aware Multibody Structure from Motion
Language: en
Pages: 194
Authors: Bullinger, Sebastian
Categories: Computers
Type: BOOK - Published: 2020-08-26 - Publisher: KIT Scientific Publishing

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"This work proposes a Multibody Structure from Motion (MSfM) algorithm for moving object reconstruction that incorporates instance-aware semantic segmentation a
Video-to-Video Face Recognition for Low-Quality Surveillance Data
Language: en
Pages: 180
Authors: Herrmann, Christian
Categories: Electronic computers. Computer science
Type: BOOK - Published: 2018-08-03 - Publisher: KIT Scientific Publishing

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The availability of video data is an opportunity and a challenge for law enforcement agencies. Face recognition methods can play a key role in the automated sea