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Nada Milisavljevic, “Sensor and Data Fusion”

The goal of this book is to provide highlights of the current research in the field of data

fusion. The book consists of twenty-five research papers, addressing various problems in

areas such as: target tracking (including adaptive sensor management, data association and

road obstacle tracking), obstacle detection for the railway traffic, real-time traffic state

estimation, air traffic control, automotive applications (e.g., car safety and driver assistance),

robotic systems, smoke detectors and home security, industrial instrumentation and process

monitoring, remote sensing (vegetation indices, update of scarce high resolution images

with time series of coarser images, land cover classification), medical imaging, anomaly

detection and behavior prediction, environmental monitoring including forest fires and

electromagnetic pollution, change detection, (distributed, wireless) sensor networks, etc. The

list of possible applications is, actually, large, since most of the methodologies presented in

the book can be adapted easily to a variety of problems and situations. The techniques

involved cover a wide range of classical or novel methods, from different Bayesian-based

approaches via Dempster-Shafer evidence theory and fuzzy logic to artificial neural

networks and multi-agent based fusion methods. Depending mainly on the technique,

different strategies for including expert knowledge and other collateral sources of

information in the fusion process are also investigated.

Altogether, the book aims to provide a valuable source of up-to-date data fusion

methods, systems, applications and tools. As such, it may be useful to researchers,

engineers, computer scientists, as well as to undergraduate and graduate students who are

interested in the latest developments in the data fusion field.

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