Road cleanliness monitoring based on deep learning

In recent years, automation and artificial intelligence have developed rapidly. Because of their adequate semantic feature extraction capabilities, deep learning models, especially deep convolutional neural networks, have been widely and successfully applied in natural scene image classification. De...

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Main Author: Yao, Ruibin
Other Authors: Wang Dan Wei
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2022
Subjects:
Online Access:https://hdl.handle.net/10356/157526
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1575262023-07-07T19:16:01Z Road cleanliness monitoring based on deep learning Yao, Ruibin Wang Dan Wei School of Electrical and Electronic Engineering yaor0001@e.ntu.edu.sg, EDWWANG@ntu.edu.sg Engineering::Electrical and electronic engineering In recent years, automation and artificial intelligence have developed rapidly. Because of their adequate semantic feature extraction capabilities, deep learning models, especially deep convolutional neural networks, have been widely and successfully applied in natural scene image classification. Deep learning-based road cleanness detection offers a lot of practical applications in the field of urban cleaning. As a result, the focus of this study is on using deep learning methods to monitor road cleanliness. Bachelor of Engineering (Electrical and Electronic Engineering) 2022-05-19T06:11:38Z 2022-05-19T06:11:38Z 2022 Final Year Project (FYP) Yao, R. (2022). Road cleanliness monitoring based on deep learning. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/157526 https://hdl.handle.net/10356/157526 en application/pdf Nanyang Technological University
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Electrical and electronic engineering
spellingShingle Engineering::Electrical and electronic engineering
Yao, Ruibin
Road cleanliness monitoring based on deep learning
description In recent years, automation and artificial intelligence have developed rapidly. Because of their adequate semantic feature extraction capabilities, deep learning models, especially deep convolutional neural networks, have been widely and successfully applied in natural scene image classification. Deep learning-based road cleanness detection offers a lot of practical applications in the field of urban cleaning. As a result, the focus of this study is on using deep learning methods to monitor road cleanliness.
author2 Wang Dan Wei
author_facet Wang Dan Wei
Yao, Ruibin
format Final Year Project
author Yao, Ruibin
author_sort Yao, Ruibin
title Road cleanliness monitoring based on deep learning
title_short Road cleanliness monitoring based on deep learning
title_full Road cleanliness monitoring based on deep learning
title_fullStr Road cleanliness monitoring based on deep learning
title_full_unstemmed Road cleanliness monitoring based on deep learning
title_sort road cleanliness monitoring based on deep learning
publisher Nanyang Technological University
publishDate 2022
url https://hdl.handle.net/10356/157526
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