Underwater target recognition methods based on the framework of deep learning: A survey

Underwater target recognition methods based on the framework of deep learning: A survey

The accuracy of underwater target recognition by autonomous underwater vehicle (AUV) is a powerful guarantee for underwater detection, rescue, and security. Recently, deep learning has made significant improvements in digital image processing for target recognition and classification, which makes th...

Full description

Bibliographic Details
Main Authors: Bowen Teng, Hongjian Zhao
Format: Article
Language:English
Published: SAGE Publishing 2020-12-01
Series:International Journal of Advanced Robotic Systems
Online Access:https://doi.org/10.1177/1729881420976307
id doaj-abeca043f57648568d2369dfe5b1137b
record_format Article
spelling doaj-abeca043f57648568d2369dfe5b1137b2020-12-17T06:03:21ZengSAGE PublishingInternational Journal of Advanced Robotic Systems1729-88142020-12-011710.1177/1729881420976307Underwater target recognition methods based on the framework of deep learning: A surveyBowen TengHongjian ZhaoThe accuracy of underwater target recognition by autonomous underwater vehicle (AUV) is a powerful guarantee for underwater detection, rescue, and security. Recently, deep learning has made significant improvements in digital image processing for target recognition and classification, which makes the underwater target recognition study becoming a hot research field. This article systematically describes the application of deep learning in underwater image analysis in the past few years and briefly expounds the basic principles of various underwater target recognition methods. Meanwhile, the applicable conditions, pros and cons of various methods are pointed out. The technical problems of AUV underwater dangerous target recognition methods are analyzed, and corresponding solutions are given. At the same time, we prospect the future development trend of AUV underwater target recognition.https://doi.org/10.1177/1729881420976307
collection DOAJ
language English
format Article
sources DOAJ
author Bowen Teng
Hongjian Zhao
spellingShingle Bowen Teng
Hongjian Zhao
Underwater target recognition methods based on the framework of deep learning: A survey
International Journal of Advanced Robotic Systems
author_facet Bowen Teng
Hongjian Zhao
author_sort Bowen Teng
title Underwater target recognition methods based on the framework of deep learning: A survey
title_short Underwater target recognition methods based on the framework of deep learning: A survey
title_full Underwater target recognition methods based on the framework of deep learning: A survey
title_fullStr Underwater target recognition methods based on the framework of deep learning: A survey
title_full_unstemmed Underwater target recognition methods based on the framework of deep learning: A survey
title_sort underwater target recognition methods based on the framework of deep learning: a survey
publisher SAGE Publishing
series International Journal of Advanced Robotic Systems
issn 1729-8814
publishDate 2020-12-01
description The accuracy of underwater target recognition by autonomous underwater vehicle (AUV) is a powerful guarantee for underwater detection, rescue, and security. Recently, deep learning has made significant improvements in digital image processing for target recognition and classification, which makes the underwater target recognition study becoming a hot research field. This article systematically describes the application of deep learning in underwater image analysis in the past few years and briefly expounds the basic principles of various underwater target recognition methods. Meanwhile, the applicable conditions, pros and cons of various methods are pointed out. The technical problems of AUV underwater dangerous target recognition methods are analyzed, and corresponding solutions are given. At the same time, we prospect the future development trend of AUV underwater target recognition.
url https://doi.org/10.1177/1729881420976307
work_keys_str_mv AT bowenteng underwatertargetrecognitionmethodsbasedontheframeworkofdeeplearningasurvey
AT hongjianzhao underwatertargetrecognitionmethodsbasedontheframeworkofdeeplearningasurvey
_version_ 1724380121676120064

Similar Items