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2022 | OriginalPaper | Chapter

34. Intelligent System for Detection and Identification of Ground Anomalies for Rescue

Authors : Antonio Dantas, Leandro Diniz, Maurício Almeida, Ella Olsson, Peter Funk, Rickard Sohlberg, Alexandre Ramos

Published in: ITNG 2022 19th International Conference on Information Technology-New Generations

Publisher: Springer International Publishing

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Abstract

The chapter delves into the importance of capturing images of the earth’s surface for various purposes, particularly in search and rescue (SAR) activities. It discusses the development of methods and tools by Brazilian and Swedish researchers to interpret soil images obtained by sensors embedded in unmanned aerial vehicles (UAVs). The challenges faced by these systems, such as adverse conditions and lighting changes, are highlighted. The chapter also presents recent works that use artificial intelligence for human detection, focusing on techniques like convolutional neural networks (CNN) and algorithms such as Single Shot MultiBox Detector (SSD) and You Only Look Once (YOLO). Additionally, it explores the methodology for identifying anomalies in images, including pre-processing techniques and the use of CNNs for efficient processing. The chapter concludes by proposing a decision support system for search and rescue, emphasizing the need for a dataset that reflects real-world scenarios.
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Metadata
Title
Intelligent System for Detection and Identification of Ground Anomalies for Rescue
Authors
Antonio Dantas
Leandro Diniz
Maurício Almeida
Ella Olsson
Peter Funk
Rickard Sohlberg
Alexandre Ramos
Copyright Year
2022
Book
ITNG 2022 19th International Conference on Information Technology-New Generations

Print ISBN: 978-3-030-97651-4

Electronic ISBN: 978-3-030-97652-1

Copyright Year: 2022

DOI
https://doi.org/10.1007/978-3-030-97652-1_34

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