Framework For Analysis And Identification Of Nonlinear Distributed Parameter Systems Using Bayesian Uncertainty Quantification Based On Generalized Polynomial Chaos
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Framework for Analysis and Identification of Nonlinear Distributed Parameter Systems using Bayesian Uncertainty Quantification based on Generalized Polynomial Chaos
Author | : Janya-anurak, Chettapong |
Publsiher | : KIT Scientific Publishing |
Total Pages | : 248 |
Release | : 2017-04-04 |
Genre | : Electronic Book |
ISBN | : 9783731506423 |
Download Framework for Analysis and Identification of Nonlinear Distributed Parameter Systems using Bayesian Uncertainty Quantification based on Generalized Polynomial Chaos Book in PDF, Epub and Kindle
Framework for Analysis and Identification of Nonlinear Distributed Parameter Systems Using Bayesian Uncertainty Quantification Based on Generalized Polynomial Chaos
Author | : Chettapong Janya-anurak |
Publsiher | : Unknown |
Total Pages | : 238 |
Release | : 2020-10-09 |
Genre | : Mathematics |
ISBN | : 1013281721 |
Download Framework for Analysis and Identification of Nonlinear Distributed Parameter Systems Using Bayesian Uncertainty Quantification Based on Generalized Polynomial Chaos Book in PDF, Epub and Kindle
In this work, the Uncertainty Quantification (UQ) approaches combined systematically to analyze and identify systems. The generalized Polynomial Chaos (gPC) expansion is applied to reduce the computational effort. The framework using gPC based on Bayesian UQ proposed in this work is capable of analyzing the system systematically and reducing the disagreement between the model predictions and the measurements of the real processes to fulfill user defined performance criteria. This work was published by Saint Philip Street Press pursuant to a Creative Commons license permitting commercial use. All rights not granted by the work's license are retained by the author or authors.
Image Based 3D Reconstruction of Dynamic Objects Using Instance Aware Multibody Structure from Motion
Author | : Bullinger, Sebastian |
Publsiher | : KIT Scientific Publishing |
Total Pages | : 194 |
Release | : 2020-08-26 |
Genre | : Computers |
ISBN | : 9783731510123 |
Download Image Based 3D Reconstruction of Dynamic Objects Using Instance Aware Multibody Structure from Motion Book in PDF, Epub and Kindle
"This work proposes a Multibody Structure from Motion (MSfM) algorithm for moving object reconstruction that incorporates instance-aware semantic segmentation and multiple view geometry methods. The MSfM pipeline tracks two-dimensional object shapes on pixel level to determine object specific feature correspondences, in order to reconstruct 3D object shapes as well as 3D object motion trajectories" -- Publicaciones de Arquitectura y Arte.
Video to Video Face Recognition for Low Quality Surveillance Data
Author | : Herrmann, Christian |
Publsiher | : KIT Scientific Publishing |
Total Pages | : 180 |
Release | : 2018-08-03 |
Genre | : Electronic computers. Computer science |
ISBN | : 9783731507994 |
Download Video to Video Face Recognition for Low Quality Surveillance Data Book in PDF, Epub and Kindle
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 search for persons in the data. This work targets efficient representations of low-quality face sequences to enable fast and accurate face search. Novel concepts for multi-scale analysis, dataset augmentation, CNN loss function, and sequence description lead to improvements over state-of-the-art methods on surveillance video footage.
Deep Learning based Vehicle Detection in Aerial Imagery
Author | : Sommer, Lars Wilko |
Publsiher | : KIT Scientific Publishing |
Total Pages | : 276 |
Release | : 2022-02-09 |
Genre | : Computers |
ISBN | : 9783731511137 |
Download Deep Learning based Vehicle Detection in Aerial Imagery Book in PDF, Epub and Kindle
This book proposes a novel deep learning based detection method, focusing on vehicle detection in aerial imagery recorded in top view. The base detection framework is extended by two novel components to improve the detection accuracy by enhancing the contextual and semantical content of the employed feature representation. To reduce the inference time, a lightweight CNN architecture is proposed as base architecture and a novel module that restricts the search area is introduced.
Dynamic Switching State Systems for Visual Tracking
Author | : Becker, Stefan |
Publsiher | : KIT Scientific Publishing |
Total Pages | : 228 |
Release | : 2020-12-02 |
Genre | : Computers |
ISBN | : 9783731510383 |
Download Dynamic Switching State Systems for Visual Tracking Book in PDF, Epub and Kindle
This work addresses the problem of how to capture the dynamics of maneuvering objects for visual tracking. Towards this end, the perspective of recursive Bayesian filters and the perspective of deep learning approaches for state estimation are considered and their functional viewpoints are brought together.
Feature Based Probabilistic Data Association for Video Based Multi Object Tracking
Author | : Grinberg, Michael |
Publsiher | : KIT Scientific Publishing |
Total Pages | : 296 |
Release | : 2018-08-10 |
Genre | : Electronic Book |
ISBN | : 9783731507819 |
Download Feature Based Probabilistic Data Association for Video Based Multi Object Tracking Book in PDF, Epub and Kindle
Facial Texture Super Resolution by Fitting 3D Face Models
Author | : Qu, Chengchao |
Publsiher | : KIT Scientific Publishing |
Total Pages | : 234 |
Release | : 2018-10-02 |
Genre | : Electronic Book |
ISBN | : 9783731508281 |
Download Facial Texture Super Resolution by Fitting 3D Face Models Book in PDF, Epub and Kindle