Reprint

Application of Multi-Sensor Fusion Technology in Target Detection and Recognition

Edited by
February 2022
168 pages
  • ISBN978-3-0365-1352-2 (Hardback)
  • ISBN978-3-0365-1351-5 (PDF)

This book is a reprint of the Special Issue Application of Multi-Sensor Fusion Technology in Target Detection and Recognition that was published in

Engineering
Environmental & Earth Sciences
Summary

Application of multi-sensor fusion technology has drawn a lot of industrial and academic interest in recent years. The multi-sensor fusion methods are widely used in many applications, such as autonomous systems, remote sensing, video surveillance, and the military. These methods can obtain the complementary properties of targets by considering multiple sensors. On the other hand, they can achieve a detailed environment description and accurate detection of interest targets based on the information from different sensors.This book collects novel developments in the field of multi-sensor, multi-source, and multi-process information fusion. Articles are expected to emphasize one or more of the three facets: architectures, algorithms, and applications. Published papers dealing with fundamental theoretical analyses, as well as those demonstrating their application to real-world problems.

Format
  • Hardback
License
© 2022 by the authors; CC BY-NC-ND license
Keywords
target detection; multi-platform imaging; spectral matching; terrestrial-hyperspectral imagery; automated image analysis; spectral library; multi-sensor fusion; object detection; deep learning; convolutional neural networks; autonomous vehicles; marine environment; target detection; co-operative; autonomous; multi-robot; USV; AUV; semantic SLAM; object detection; YOLOv3; object based map; EKF; specular reflection detection; specular reflection inpainting; transparent object; multispectral polarimetric imagery; light field; maritime vessel dataset; ship detection; object detection; convolutional neural network; deep learning; autonomous marine navigation; machine learning; inversion; ocean colour; phytoplankton; pigment vertical profile; deep chlorophyll maximum; Tara Oceans; MAREDAT; pigments; ITCOMP-SOM; Self Organizing Maps