Multistrengthening Module-Based Salient Object Detection

Object detection is a classical research problem in computer vision, and it is widely used in the automatic monitoring field of various production safety. However, current object detection techniques often suffer low detection accuracy when an image has a complex background. To solve this problem, t...

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Autores principales:	Qian Zhao, Haifeng Wang, Junpeng Dang, Songlin Li, Rong Chang, Yanbin Fang, Zhi Zhang, Jie Peng, Yang Yang
Formato:	article
Lenguaje:	EN
Publicado:	Hindawi Limited 2021
Materias:	Engineering (General). Civil engineering (General) TA1-2040 Mathematics QA1-939
Acceso en línea:	https://doaj.org/article/d86a278775074e87af483b437ae24ccd
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id	oai:doaj.org-article:d86a278775074e87af483b437ae24ccd
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spelling	oai:doaj.org-article:d86a278775074e87af483b437ae24ccd2021-11-15T01:19:54ZMultistrengthening Module-Based Salient Object Detection1563-514710.1155/2021/2472676https://doaj.org/article/d86a278775074e87af483b437ae24ccd2021-01-01T00:00:00Zhttp://dx.doi.org/10.1155/2021/2472676https://doaj.org/toc/1563-5147Object detection is a classical research problem in computer vision, and it is widely used in the automatic monitoring field of various production safety. However, current object detection techniques often suffer low detection accuracy when an image has a complex background. To solve this problem, this paper proposes a double U-shaped multireinforced unit structure network (DUMRN). The proposed network consists of a detection module (DM), a reinforced module (RM), and a salient loss function (SLF). Extensive experiments on five public datasets and a practical application dataset are conducted and compared against nine state-of-the-art methods. The experiment results show the superiority of our method over the state of the art.Qian ZhaoHaifeng WangJunpeng DangSonglin LiRong ChangYanbin FangZhi ZhangJie PengYang YangHindawi LimitedarticleEngineering (General). Civil engineering (General)TA1-2040MathematicsQA1-939ENMathematical Problems in Engineering, Vol 2021 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Engineering (General). Civil engineering (General) TA1-2040 Mathematics QA1-939
spellingShingle	Engineering (General). Civil engineering (General) TA1-2040 Mathematics QA1-939 Qian Zhao Haifeng Wang Junpeng Dang Songlin Li Rong Chang Yanbin Fang Zhi Zhang Jie Peng Yang Yang Multistrengthening Module-Based Salient Object Detection
description	Object detection is a classical research problem in computer vision, and it is widely used in the automatic monitoring field of various production safety. However, current object detection techniques often suffer low detection accuracy when an image has a complex background. To solve this problem, this paper proposes a double U-shaped multireinforced unit structure network (DUMRN). The proposed network consists of a detection module (DM), a reinforced module (RM), and a salient loss function (SLF). Extensive experiments on five public datasets and a practical application dataset are conducted and compared against nine state-of-the-art methods. The experiment results show the superiority of our method over the state of the art.
format	article
author	Qian Zhao Haifeng Wang Junpeng Dang Songlin Li Rong Chang Yanbin Fang Zhi Zhang Jie Peng Yang Yang
author_facet	Qian Zhao Haifeng Wang Junpeng Dang Songlin Li Rong Chang Yanbin Fang Zhi Zhang Jie Peng Yang Yang
author_sort	Qian Zhao
title	Multistrengthening Module-Based Salient Object Detection
title_short	Multistrengthening Module-Based Salient Object Detection
title_full	Multistrengthening Module-Based Salient Object Detection
title_fullStr	Multistrengthening Module-Based Salient Object Detection
title_full_unstemmed	Multistrengthening Module-Based Salient Object Detection
title_sort	multistrengthening module-based salient object detection
publisher	Hindawi Limited
publishDate	2021
url	https://doaj.org/article/d86a278775074e87af483b437ae24ccd
work_keys_str_mv	AT qianzhao multistrengtheningmodulebasedsalientobjectdetection AT haifengwang multistrengtheningmodulebasedsalientobjectdetection AT junpengdang multistrengtheningmodulebasedsalientobjectdetection AT songlinli multistrengtheningmodulebasedsalientobjectdetection AT rongchang multistrengtheningmodulebasedsalientobjectdetection AT yanbinfang multistrengtheningmodulebasedsalientobjectdetection AT zhizhang multistrengtheningmodulebasedsalientobjectdetection AT jiepeng multistrengtheningmodulebasedsalientobjectdetection AT yangyang multistrengtheningmodulebasedsalientobjectdetection
_version_	1718428952342560768

Multistrengthening Module-Based Salient Object Detection

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