Space Object Identification Using Spatio Temporal Pattern Recognition
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Space Object Identification Using Spatio Temporal Pattern Recognition
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Author : Gary W. Brandstorm
language : en
Publisher:
Release Date : 1995
Space Object Identification Using Spatio Temporal Pattern Recognition written by Gary W. Brandstorm and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1995 with Artificial satellites categories.
Space Object Identification Using Spatio Temporal Pattern Recognition
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Author : Gary W. Brandstorm
language : en
Publisher:
Release Date : 1995
Space Object Identification Using Spatio Temporal Pattern Recognition written by Gary W. Brandstorm and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1995 with Artificial satellites categories.
Space Object Identification Using Spatial Pattern Recognition
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Author : Paul E. Silversmith
language : en
Publisher:
Release Date : 2014
Space Object Identification Using Spatial Pattern Recognition written by Paul E. Silversmith and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014 with categories.
The traditional method of determining spacecraft attitude with a star tracker is by comparing the angle measurements between stars within a certain field-of-view (FOV) with that of angle measurements in a catalog. This technique is known as the angle method. A new approach, the planar triangle method (PTM), uses the properties of planar triangles to compare stars in a FOV with stars in a catalog. Specifically, the area and polar moment of planar triangle combinations are the comparison parameters used in the method. The PTM has been shown to provide a more consistent success rate than that of the traditional angle method. The work herein presents a technique of data association through the use of the planar triangle method. Instead of comparing the properties of stars with that of a catalog, a comparison is made between the properties of resident space objects (RSOs) and a catalog comprised of Fengyun 1C debris data and simulated data. It is shown that the planar triangle method is effective in RSO identification and is robust to the presence of measurement and sensor error.
Space Object Identification Using Feature Space Trajectory Neural Networks
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Author : Neal W. Bruegger
language : en
Publisher:
Release Date : 1997-03-01
Space Object Identification Using Feature Space Trajectory Neural Networks written by Neal W. Bruegger and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1997-03-01 with Artificial satellites categories.
The Feature Space Trajectory Neural Network (FSTNN) is a simple yet powerful pattern recognition tool developed by Neiberg and Casasent for use in an Automatic Target Recognition System. Since the FSTNN was developed, it has been used on various problems including speaker identification and space object identification. However, in these types of problems, the test set represents time series data rather than an independent set of points. Since the distance metric of the standard FSTNN treats each test point independently without regard to its position in the sequence, the FSTNN can yield less than optimal results in these problems. Two methods for incorporating sequence information into the FSTNN algorithm are presented. These methods, Dynamic Time Warping (DTW) and Uniform Time Warping (UTW), are described and compared to the standard FSTNN performance on the space object identification problem. Both reduce error induced by improper synchronization of the test and training sequences and make the FSTNN more generally applicable to a wide variety of pattern recognition problems. They incorporate sequencing information by synchronizing the test and training trajectories. DTW accomplishes this 'on-the-fly' as the sequence progresses while UTW uniformly compensates for temporal differences across the trajectories. These algorithms improve the maximum probability of false alarm (PFA) of the standard FSTNN by an average of 10.18% and 27.69%, respectively, although UTW is less consistent in its results. A metric for determining the saliency of the features in an FSTNN is also presented and demonstrated.
Spatio Temporal Pattern Recognition Using Hidden Markov Models
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Author :
language : en
Publisher:
Release Date : 1994
Spatio Temporal Pattern Recognition Using Hidden Markov Models written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1994 with categories.
A new spatio-temporal method for identifying 3D objects found in 2D image sequences is presented. The Hidden Markov Model technique is used as a spatio-temporal classification algorithm to identify 3D objects by the temporal changes in observed shape features. A new information theoretic argument is developed that proves identifying objects based on image sequences can lead to higher classification accuracies than single look methods. A new distance measure is proposed that analyzes the performance of Hidden Markov Models in a multi-class pattern recognition problem. A three class problem identifying moving light display objects provides experimental verification of the sequence processing argument. Individual frames of a MLD image sequence contain very little spatial information. The single look classification rate for the moving light display imagery was observed to be near 50%. In contrast, the Hidden Markov Model classification rate was above 93 %. The alternate nearest neighbor multiple frame technique classification rate was 20% below the Hidden Markov Models. A one sided t-test revealed a highly statistically significant difference between the Hidden Markov Model and multiple frame technique at a 0. 01 level of significance. A five class problem consisting of tactical military ground vehicles is considered to provide verification using imagery with both spatial and temporal information. Results confirmed the new spatio-temporal pattern recognition method produces superior results by accessing the temporal information in the image sequences. A prototype automatic target recognition system is demonstrated. Hidden Markov model, Pattern recognition, Motion analysis, Signal processing.
Pattern Recognition
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Author : Björn Andres
language : en
Publisher: Springer Nature
Release Date : 2022-09-22
Pattern Recognition written by Björn Andres and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-09-22 with Computers categories.
This book constitutes the refereed proceedings of the 44th DAGM German Conference on Pattern Recognition, DAGM GCPR 2022, which was held during September 27 – 30, 2022. The 37 papers presented in this volume were carefully reviewed and selected from 78 submissions. They were organized in topical sections as follows: machine learning methods; unsupervised, semi-supervised and transfer learning; interpretable machine learning; low-level vision and computational photography; motion, pose estimation and tracking; 3D vision and stereo; detection and recognition; language and vision; scene understanding; photogrammetry and remote sensing; pattern recognition in the life and natural sciences; systems and applications.
Proceedings Of The 16th International Conference On Hybrid Intelligent Systems His 2016
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Author : Ajith Abraham
language : en
Publisher: Springer
Release Date : 2017-02-21
Proceedings Of The 16th International Conference On Hybrid Intelligent Systems His 2016 written by Ajith Abraham and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-02-21 with Technology & Engineering categories.
This book presents the latest research in hybrid intelligent systems. It includes 57 carefully selected papers from the 16th International Conference on Hybrid Intelligent Systems (HIS 2016) and the 8th World Congress on Nature and Biologically Inspired Computing (NaBIC 2016), held on November 21–23, 2016 in Marrakech, Morocco. HIS - NaBIC 2016 was jointly organized by the Machine Intelligence Research Labs (MIR Labs), USA; Hassan 1st University, Settat, Morocco and University of Sfax, Tunisia. Hybridization of intelligent systems is a promising research field in modern artificial/computational intelligence and is concerned with the development of the next generation of intelligent systems. The conference’s main aim is to inspire further exploration of the intriguing potential of hybrid intelligent systems and bio-inspired computing. As such, the book is a valuable resource for practicing engineers /scientists and researchers working in the field of computational intelligence and artificial intelligence.
Pattern Recognition Technologies And Applications Recent Advances
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Author : Verma, Brijesh
language : en
Publisher: IGI Global
Release Date : 2008-06-30
Pattern Recognition Technologies And Applications Recent Advances written by Verma, Brijesh and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-06-30 with Computers categories.
The nature of handwriting in our society has significantly altered over the ages due to the introduction of new technologies such as computers and the World Wide Web. With increases in the amount of signature verification needs, state of the art internet and paper-based automated recognition methods are necessary. Pattern Recognition Technologies and Applications: Recent Advances provides cutting-edge pattern recognition techniques and applications. Written by world-renowned experts in their field, this easy to understand book is a must have for those seeking explanation in topics such as on- and offline handwriting and speech recognition, signature verification, and gender classification.
Pattern Recognition And Image Analysis
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Author : Luís A. Alexandre
language : en
Publisher: Springer
Release Date : 2017-06-08
Pattern Recognition And Image Analysis written by Luís A. Alexandre and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-06-08 with Computers categories.
This book constitutes the refereed proceedings of the 8th Iberian Conference on Pattern Recognition and Image Analysis, IbPRIA 2017, held in Faro, Portugal, in June 2017. The 60 regular papers presented in this volume were carefully reviewed and selected from 86 submissions. They are organized in topical sections named: Pattern Recognition and Machine Learning; Computer Vision; Image and Signal Processing; Medical Image; and Applications.
International Aerospace Abstracts
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Author :
language : en
Publisher:
Release Date : 1999
International Aerospace Abstracts written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999 with Aeronautics categories.