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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2022
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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 |
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Engineering::Electrical and electronic engineering Yao, Ruibin Road cleanliness monitoring based on deep learning |
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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. |
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Wang Dan Wei |
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Wang Dan Wei Yao, Ruibin |
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Final Year Project |
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Yao, Ruibin |
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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 |
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Road cleanliness monitoring based on deep learning |
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Road cleanliness monitoring based on deep learning |
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road cleanliness monitoring based on deep learning |
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Nanyang Technological University |
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2022 |
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https://hdl.handle.net/10356/157526 |
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1772826095566979072 |