Multisensor Fusion For Computer Vision PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Multisensor Fusion For Computer Vision PDF full book. Access full book title Multisensor Fusion For Computer Vision.
Author | : J. K. Aggarwal |
Publisher | : Springer Science & Business Media |
Total Pages | : 449 |
Release | : 2013-06-29 |
Genre | : Computers |
ISBN | : 366202957X |
Download Multisensor Fusion for Computer Vision Book in PDF, ePub and Kindle
This volume contains revised papers based on contributions to the NATO Advanced Research Workshop on Multisensor Fusion for Computer Vision, held in Grenoble, France, in June 1989. The 24 papers presented here cover a broad range of topics, including the principles and issues in multisensor fusion, information fusion for navigation, multisensor fusion for object recognition, network approaches to multisensor fusion, computer architectures for multi sensor fusion, and applications of multisensor fusion. The participants met in the beautiful surroundings of Mont Belledonne in Grenoble to discuss their current work in a setting conducive to interaction and the exchange of ideas. Each participant is a recognized leader in his or her area in the academic, governmental, or industrial research community. The workshop focused on techniques for the fusion or integration of sensor information to achieve the optimum interpretation of a scene. Several participants presented novel points of view on the integration of information. The 24 papers presented in this volume are based on those collected by the editor after the workshop, and reflect various aspects of our discussions. The papers are organized into five parts, as follows.
Author | : Xinyu Zhang |
Publisher | : Springer Nature |
Total Pages | : 237 |
Release | : |
Genre | : |
ISBN | : 9819932807 |
Download Multi-sensor Fusion for Autonomous Driving Book in PDF, ePub and Kindle
Author | : H.B. Mitchell |
Publisher | : Springer Science & Business Media |
Total Pages | : 281 |
Release | : 2007-07-13 |
Genre | : Technology & Engineering |
ISBN | : 3540715592 |
Download Multi-Sensor Data Fusion Book in PDF, ePub and Kindle
This textbook provides a comprehensive introduction to the theories and techniques of multi-sensor data fusion. It is aimed at advanced undergraduate and first-year graduate students in electrical engineering and computer science, as well as researchers and professional engineers. The book is intended to be self-contained. No previous knowledge of multi-sensor data fusion is assumed, although some familiarity with the basic tools of linear algebra, calculus and simple probability theory is recommended.
Author | : Avinash C. Kak |
Publisher | : Morgan Kaufmann |
Total Pages | : 460 |
Release | : 1987 |
Genre | : Computers |
ISBN | : 9780934613590 |
Download Spatial Reasoning and Multi-Sensor Fusion Book in PDF, ePub and Kindle
Spatial Reasoning and Multi-Sensor Fusion
Author | : Ren C. Luo |
Publisher | : Intellect Books |
Total Pages | : 736 |
Release | : 1995 |
Genre | : Computers |
ISBN | : |
Download Multisensor Integration and Fusion for Intelligent Machines and Systems Book in PDF, ePub and Kindle
There has been a growing interest during the 1990s in the use of multiple sensors to increase the capabilities of intelligent machines and systems. This text is a compendium of some of the most important and influential work that has appeared in this area. In addition, it contains comprehensive introductory material and an extensive survey and review of related research. The volume should be useful to everyone interested in the development of more intelligent machines and systems through the synergistic use of multiple sensors.
Author | : Bogdan Ionescu |
Publisher | : Springer Science & Business Media |
Total Pages | : 279 |
Release | : 2014-03-25 |
Genre | : Computers |
ISBN | : 3319056964 |
Download Fusion in Computer Vision Book in PDF, ePub and Kindle
This book presents a thorough overview of fusion in computer vision, from an interdisciplinary and multi-application viewpoint, describing successful approaches, evaluated in the context of international benchmarks that model realistic use cases. Features: examines late fusion approaches for concept recognition in images and videos; describes the interpretation of visual content by incorporating models of the human visual system with content understanding methods; investigates the fusion of multi-modal features of different semantic levels, as well as results of semantic concept detections, for example-based event recognition in video; proposes rotation-based ensemble classifiers for high-dimensional data, which encourage both individual accuracy and diversity within the ensemble; reviews application-focused strategies of fusion in video surveillance, biomedical information retrieval, and content detection in movies; discusses the modeling of mechanisms of human interpretation of complex visual content.
Author | : Zhiqin Zhu |
Publisher | : Frontiers Media SA |
Total Pages | : 207 |
Release | : 2023-10-25 |
Genre | : Science |
ISBN | : 283253693X |
Download Multi-Sensor Imaging and Fusion: Methods, Evaluations, and Applications Book in PDF, ePub and Kindle
Author | : |
Publisher | : |
Total Pages | : 120 |
Release | : 1988 |
Genre | : |
ISBN | : |
Download Проблемы управления трудовыми ресурсами Book in PDF, ePub and Kindle
Author | : Michael Yang |
Publisher | : Academic Press |
Total Pages | : 422 |
Release | : 2019-07-16 |
Genre | : Computers |
ISBN | : 0128173599 |
Download Multimodal Scene Understanding Book in PDF, ePub and Kindle
Multimodal Scene Understanding: Algorithms, Applications and Deep Learning presents recent advances in multi-modal computing, with a focus on computer vision and photogrammetry. It provides the latest algorithms and applications that involve combining multiple sources of information and describes the role and approaches of multi-sensory data and multi-modal deep learning. The book is ideal for researchers from the fields of computer vision, remote sensing, robotics, and photogrammetry, thus helping foster interdisciplinary interaction and collaboration between these realms. Researchers collecting and analyzing multi-sensory data collections – for example, KITTI benchmark (stereo+laser) - from different platforms, such as autonomous vehicles, surveillance cameras, UAVs, planes and satellites will find this book to be very useful. Contains state-of-the-art developments on multi-modal computing Shines a focus on algorithms and applications Presents novel deep learning topics on multi-sensor fusion and multi-modal deep learning
Author | : Ni-Bin Chang |
Publisher | : CRC Press |
Total Pages | : 627 |
Release | : 2018-02-21 |
Genre | : Technology & Engineering |
ISBN | : 1351650637 |
Download Multisensor Data Fusion and Machine Learning for Environmental Remote Sensing Book in PDF, ePub and Kindle
In the last few years the scientific community has realized that obtaining a better understanding of interactions between natural systems and the man-made environment across different scales demands more research efforts in remote sensing. An integrated Earth system observatory that merges surface-based, air-borne, space-borne, and even underground sensors with comprehensive and predictive capabilities indicates promise for revolutionizing the study of global water, energy, and carbon cycles as well as land use and land cover changes. The aim of this book is to present a suite of relevant concepts, tools, and methods of integrated multisensor data fusion and machine learning technologies to promote environmental sustainability. The process of machine learning for intelligent feature extraction consists of regular, deep, and fast learning algorithms. The niche for integrating data fusion and machine learning for remote sensing rests upon the creation of a new scientific architecture in remote sensing science that is designed to support numerical as well as symbolic feature extraction managed by several cognitively oriented machine learning tasks at finer scales. By grouping a suite of satellites with similar nature in platform design, data merging may come to help for cloudy pixel reconstruction over the space domain or concatenation of time series images over the time domain, or even both simultaneously. Organized in 5 parts, from Fundamental Principles of Remote Sensing; Feature Extraction for Remote Sensing; Image and Data Fusion for Remote Sensing; Integrated Data Merging, Data Reconstruction, Data Fusion, and Machine Learning; to Remote Sensing for Environmental Decision Analysis, the book will be a useful reference for graduate students, academic scholars, and working professionals who are involved in the study of Earth systems and the environment for a sustainable future. The new knowledge in this book can be applied successfully in many areas of environmental science and engineering.