Sensor Fusion and its Applications
eBook - PDF

Sensor Fusion and its Applications

  1. 496 pages
  2. English
  3. PDF
  4. Available on iOS & Android
eBook - PDF

Sensor Fusion and its Applications

About this book

This book aims to explore the latest practices and research works in the area of sensor fusion. The book intends to provide a collection of novel ideas, theories, and solutions related to the research areas in the field of sensor fusion. This book is a unique, comprehensive, and up-to-date resource for sensor fusion systems designers. This book is appropriate for use as an upper division undergraduate or graduate level text book. It should also be of interest to researchers, who need to process and interpret the sensor data in most scientific and engineering fields. The initial chapters in this book provide a general overview of sensor fusion. The later chapters focus mostly on the applications of sensor fusion. Much of this work has been published in refereed journals and conference proceedings and these papers have been modified and edited for content and style. With contributions from the world's leading fusion researchers and academicians, this book has 22 chapters covering the fundamental theory and cutting-edge developments that are driving this field.

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Yes, you can access Sensor Fusion and its Applications by Ciza Thomas in PDF and/or ePUB format, as well as other popular books in Computer Science & Optical Data Processing. We have over one million books available in our catalogue for you to explore.

Table of contents

  1. Sensor Fusion and its Applications
  2. Contents
  3. Preface
  4. Chapter 1 - State Optimal Estimation for Nonstandard Multi-sensor Information Fusion System
  5. Chapter 2 - Air traffic trajectories segmentation based on time-series sensor data
  6. Chapter 3 - Distributed Compressed Sensing of Sensor Data
  7. Chapter 4 - Adaptive Kalman Filter for Navigation Sensor Fusion
  8. Chapter 5 Fusion of Images Recordedwith Variable Illumination
  9. Chapter 6 - Camera and laser robust integration in engineering and architecture applications
  10. Chapter 7 - Spatial Voting With Data Modeling
  11. Chapter 8 - Hidden Markov Model as a Framework for Situational Awareness
  12. Chapter 9 - Multi-sensorial Active Perception for Indoor Environment Modeling
  13. Chapter 10 - Mathematical Basis of Sensor Fusion in Intrusion Detection Systems
  14. Chapter 11 - Sensor Fusion for Position Estimation in Networked Systems
  15. Chapter 12 - M2SIR: A Multi Modal Sequential Importance Resampling Algorithm for Particle Filters
  16. Chapter 13 - On passive emitter tracking in sensor networks
  17. Chapter 14 - Fuzzy-Pattern-Classifier Based Sensor Fusion for Machine Conditioning
  18. Chapter 15 - Feature extraction: techniques for landmark based navigation system
  19. Chapter 16 - Sensor Data Fusion for Road Obstacle Detection: A Validation Framework
  20. Chapter 17 - Biometrics Sensor Fusion
  21. Chapter 18 - Fusion of Odometry and Visual Datas to Localization a Mobile Robot
  22. Chapter 19 - Probabilistic Mapping by Fusion of Range-Finders Sensors and Odometry
  23. Chapter 20 - Sensor fusion for electromagnetic stress measurement and material characterisation
  24. Chapter 21 - Iterative Multiscale Fusion and Night Vision Colorization of Multispectral Images
  25. Chapter 22 - Super-Resolution Reconstruction by Image Fusion and Application to Surveillance Videos Captured by Small Unmanned Aircraft Systems