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Multi-Sensor Data Fusion with MATLAB by Jitendra R. Raol

Multi-Sensor Data Fusion with MATLAB Jitendra R. Raol ebook
Page: 568
Format: pdf
ISBN: 1439800030, 9781439800034
Publisher:

Research experience in image processing, computer vision or machine learning is desirable. And ships) detection, categorisation and tracking using a heterogeneous UAV sensor network. Jul 1, 2013 - Multi-Sensor Data Fusion with MATLAB Jitendra R. Mitchell 2007 1 3540714634,9783540714637. An important issue in applying a proper approach is computational complexity. Multi-Sensor Data Fusion: An Introduction H.B. There are several mathematical approaches to combine the observations of multiple sensors by use of Kalman filter. Good programming skills are required, preferably with Matlab and C++. In this paper, four data fusion algorithms based on Kalman filter are considered including three centralized and one decentralized methods. Raol 2009 1439800030,9781439800034. Using MATLAB, computational loads of these methods are compared while number of sensors increases. In particular, the job will involve the development of novel computer vision and machine learning algorithms for sensor alignment, super-resolution, data fusion, and active learning from human feedback. Mar 24, 2014 - GO Multi-Sensor Data Fusion with MATLABAuthor: Jitendra R.