2017 Symposium On Sensor Data Fusion Trends Solutions Applications Sdf
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2017 Sensor Data Fusion Trends Solutions Applications Sdf
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Author : IEEE Staff
language : en
Publisher:
Release Date : 2017-10-10
2017 Sensor Data Fusion Trends Solutions Applications Sdf written by IEEE Staff and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-10-10 with categories.
Sensor Data Fusion techniques provide higher level information by spatio temporal data integration, the exploitation of redundant and complementary information, and the available context Important applications exist in logistics, advanced driver assistance systems, medical care, public security, defence, aerospace, robotics, industrial production, precision agriculture, traffic monitoring, sensor positioning, and resource management
8th Workshop On Sensor Data Fusion
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Author : Institute of Electrical and Electronics Engineers
language : en
Publisher:
Release Date : 2013
8th Workshop On Sensor Data Fusion written by Institute of Electrical and Electronics Engineers and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013 with Multisensor data fusion categories.
2013 Workshop On Sensor Data Fusion
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Author : IEEE Staff
language : en
Publisher:
Release Date : 2013-10-09
2013 Workshop On Sensor Data Fusion written by IEEE Staff and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-10-09 with categories.
2012 Workshop On Sensor Data Fusion Trends Solutions Applications Sdf
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Author : IEEE Staff
language : en
Publisher:
Release Date : 2012
2012 Workshop On Sensor Data Fusion Trends Solutions Applications Sdf written by IEEE Staff and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012 with categories.
Multisensor Fusion And Integration In The Wake Of Big Data Deep Learning And Cyber Physical System
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Author : Sukhan Lee
language : en
Publisher: Springer
Release Date : 2018-07-04
Multisensor Fusion And Integration In The Wake Of Big Data Deep Learning And Cyber Physical System written by Sukhan Lee and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-07-04 with Technology & Engineering categories.
This book includes selected papers from the 13th IEEE International Conference on Multisensor Integration and Fusion for Intelligent Systems (MFI 2017) held in Daegu, Korea, November 16–22, 2017. It covers various topics, including sensor/actuator networks, distributed and cloud architectures, bio-inspired systems and evolutionary approaches, methods of cognitive sensor fusion, Bayesian approaches, fuzzy systems and neural networks, biomedical applications, autonomous land, sea and air vehicles, localization, tracking, SLAM, 3D perception, manipulation with multifinger hands, robotics, micro/nano systems, information fusion and sensors, and multimodal integration in HCI and HRI. The book is intended for robotics scientists, data and information fusion scientists, researchers and professionals at universities, research institutes and laboratories.
Proceedings Of The 7th International Symposium Of Space Optical Instruments And Applications
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Author : H. Paul Urbach
language : en
Publisher: Springer Nature
Release Date : 2023-10-01
Proceedings Of The 7th International Symposium Of Space Optical Instruments And Applications written by H. Paul Urbach and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-10-01 with Science categories.
This proceedings book contains selected and expanded contributions presented at the 7th International Symposium of Space Optical Instruments and Applications, held in Beijing, China, on Oct 21–23, 2022. The meeting was organized by the Sino-Holland Space Optical Instruments Joint Laboratory and supported by Beijing Institute and Space Mechanics and Electricity. In the recent years, space optical payloads are advancing toward high spatial resolution, high temporal resolution, high radiometric resolution, and high spectral resolution and becoming more and more intelligent. Commercial remote sensing industry has made steady progress in terms of the scope of satellite systems and applications. Meanwhile, space optical remote sensing data has been extensively applied to monitoring of resources, meteorology, ocean, environment, disaster reduction, and many other fields. The symposium focused on key innovations of space-based optical instruments and applications and the newest developments in theory, technology, and applications in optics, in both China and Europe. It thus provided a platform for exchanges on the latest research and current and planned optical missions. The major topics covered in these conference proceedings are: 1) Advanced space optical remote sensing application technology. 2) Deep space exploration and astronomical observation technology. 3) Advanced space optical remote sensing instrument technology. 4) Commercial optical observation technology and services.
2015 Sensor Data Fusion Trends Solutions Applications Sdf 2015
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Author :
language : en
Publisher:
Release Date : 2015
2015 Sensor Data Fusion Trends Solutions Applications Sdf 2015 written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015 with categories.
Proceedings Of The 21st Eann Engineering Applications Of Neural Networks 2020 Conference
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Author : Lazaros Iliadis
language : en
Publisher: Springer Nature
Release Date : 2020-05-27
Proceedings Of The 21st Eann Engineering Applications Of Neural Networks 2020 Conference written by Lazaros Iliadis and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-05-27 with Computers categories.
This book gathers the proceedings of the 21st Engineering Applications of Neural Networks Conference, which is supported by the International Neural Networks Society (INNS). Artificial Intelligence (AI) has been following a unique course, characterized by alternating growth spurts and “AI winters.” Today, AI is an essential component of the fourth industrial revolution and enjoying its heyday. Further, in specific areas, AI is catching up with or even outperforming human beings. This book offers a comprehensive guide to AI in a variety of areas, concentrating on new or hybrid AI algorithmic approaches with robust applications in diverse sectors. One of the advantages of this book is that it includes robust algorithmic approaches and applications in a broad spectrum of scientific fields, namely the use of convolutional neural networks (CNNs), deep learning and LSTM in robotics/machine vision/engineering/image processing/medical systems/the environment; machine learning and meta learning applied to neurobiological modeling/optimization; state-of-the-art hybrid systems; and the algorithmic foundations of artificial neural networks.
Machine Learning And Autonomous Systems
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Author : Joy Iong-Zong Chen
language : en
Publisher: Springer Nature
Release Date : 2022-02-10
Machine Learning And Autonomous Systems written by Joy Iong-Zong Chen and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-02-10 with Technology & Engineering categories.
This book involves a collection of selected papers presented at International Conference on Machine Learning and Autonomous Systems (ICMLAS 2021), held in Tamil Nadu, India, during 24–25 September 2021. It includes novel and innovative work from experts, practitioners, scientists and decision-makers from academia and industry. It covers selected papers in the area of emerging modern mobile robotic systems and intelligent information systems and autonomous systems in agriculture, health care, education, military and industries.
Simulation Of Automotive Radar Point Clouds In Standardized Frameworks
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Author : Thomas Eder
language : en
Publisher: Cuvillier Verlag
Release Date : 2021-11-24
Simulation Of Automotive Radar Point Clouds In Standardized Frameworks written by Thomas Eder and has been published by Cuvillier Verlag this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-11-24 with Technology & Engineering categories.
The simulation of the vehicle’s environmental sensors, the so-called sensor simulation, is crucial for testing and validating autonomous driving. Automobile manufacturers are increasingly focusing on a standardized architecture with a high level of abstraction. In order to simulate the sensors, such as radar sensors, most realistically on a point cloud level, data-based methods are used in many cases. In general, and specifically in case of radar sensors, there are still challenges to be faced. Therefore, four research questions are addressed: Is it possible to generate synthetic training data for data-based models? Which statistical approaches are suitable to simulate radar point clouds and how shall their learning capacities be evaluated? Is there a modeling approach to circumvent the disadvantages of statistical modeling? How to tackle the statistical nature of radar sensors during validation? Die Simulation der Umfeldsensoren des Fahrzeugs, die sogenannte Sensorsimulation, ist für Test und Absicherung des autonomen Fahrens entscheidend. Die Automobilhersteller setzen dabei zunehmend auf eine standardisierte Architektur mit hohem Abstraktionsgrad. Um die Sensoren, wie z.B. Radarsensoren, möglichst realitätsnah auf Punktwolkenebene zu simulieren, werden in vielen Fällen datenbasierte Methoden eingesetzt. Im Allgemeinen und speziell im Fall von Radarsensoren gilt es noch immer zahlreiche Herausforderungen zu meistern. Daher werden in dieser Arbeit vier Forschungsfragen behandelt: Können synthetische Trainingsdaten für datenbasierte Modelle generiert werden? Welche statistischen Ansätze sind geeignet, um Radar-Punktwolken zu simulieren und wie können die Ansätze bewertet werden? Gibt es einen Modellierungsansatz, um Nachteile der statistischen Modellierung zu umgehen? Wie kann die statistische Natur bei der Validierung berücksichtigt werden?