DESIGN AND DEVELOPMENT OF A SCENE RECOGNITION SYSTEM USING NEURAL NETWORK MODELS
Scene recognition has become one of the challenging aspects in machine learning. Not only that the performance of a state-of-art scene recognition system is bad, but it also requires a powerful computational device in order to carry out tasks. Hence, the central objective of this research is to desi...
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| Format: | Final Year Project Report / IMRAD |
| Language: | en en |
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Universiti Malaysia Sarawak (UNIMAS)
2020
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| Online Access: | http://ir.unimas.my/id/eprint/32949/1/Ong%20Hui%20Xin%20-%2024%20pgs.pdf http://ir.unimas.my/id/eprint/32949/4/Ong%20Hui%20Xin%20ft.pdf http://ir.unimas.my/id/eprint/32949/ |
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| _version_ | 1831811290442498048 |
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| author | Ong, Hui Xin |
| author_facet | Ong, Hui Xin |
| author_sort | Ong, Hui Xin |
| building | Centre for Academic Information Services (CAIS) |
| collection | Institutional Repository |
| content_provider | Universiti Malaysia Sarawak |
| content_source | UNIMAS Institutional Repository |
| continent | Asia |
| country | Malaysia |
| description | Scene recognition has become one of the challenging aspects in machine learning. Not only that the performance of a state-of-art scene recognition system is bad, but it also requires a powerful computational device in order to carry out tasks. Hence, the central objective of this research is to design a new scene recognition system that performs well, at the same time reduce
computational load of a scene recognition system. The biggest modification of the new scene recognition system is that it extracts objects as attributes for a classifier to perform scene classification. It also combines an object detection Convolutional Neural Network (CNN) model and a classifier. The method is simple, as it uses low computational power but also makes the scene recognition system perform well. There are two experiments done in this research to illustrate the performance of the new scene recognition system
analysed. From the experiments done to classify different scene classes, it shows good performances of 97.11% and 80.22% of accuracy in classifying two distinct scene classes and three similar scene classes respectively. |
| format | Final Year Project Report / IMRAD |
| id | my.unimas.ir-32949 |
| institution | Universiti Malaysia Sarawak |
| language | en en |
| publishDate | 2020 |
| publisher | Universiti Malaysia Sarawak (UNIMAS) |
| record_format | eprints |
| spelling | my.unimas.ir-329492024-02-20T04:30:31Z http://ir.unimas.my/id/eprint/32949/ DESIGN AND DEVELOPMENT OF A SCENE RECOGNITION SYSTEM USING NEURAL NETWORK MODELS Ong, Hui Xin H Social Sciences (General) QA76 Computer software Scene recognition has become one of the challenging aspects in machine learning. Not only that the performance of a state-of-art scene recognition system is bad, but it also requires a powerful computational device in order to carry out tasks. Hence, the central objective of this research is to design a new scene recognition system that performs well, at the same time reduce computational load of a scene recognition system. The biggest modification of the new scene recognition system is that it extracts objects as attributes for a classifier to perform scene classification. It also combines an object detection Convolutional Neural Network (CNN) model and a classifier. The method is simple, as it uses low computational power but also makes the scene recognition system perform well. There are two experiments done in this research to illustrate the performance of the new scene recognition system analysed. From the experiments done to classify different scene classes, it shows good performances of 97.11% and 80.22% of accuracy in classifying two distinct scene classes and three similar scene classes respectively. Universiti Malaysia Sarawak (UNIMAS) 2020 Final Year Project Report / IMRAD NonPeerReviewed text en http://ir.unimas.my/id/eprint/32949/1/Ong%20Hui%20Xin%20-%2024%20pgs.pdf text en http://ir.unimas.my/id/eprint/32949/4/Ong%20Hui%20Xin%20ft.pdf Ong, Hui Xin (2020) DESIGN AND DEVELOPMENT OF A SCENE RECOGNITION SYSTEM USING NEURAL NETWORK MODELS. [Final Year Project Report / IMRAD] (Unpublished) |
| spellingShingle | H Social Sciences (General) QA76 Computer software Ong, Hui Xin DESIGN AND DEVELOPMENT OF A SCENE RECOGNITION SYSTEM USING NEURAL NETWORK MODELS |
| title | DESIGN AND DEVELOPMENT OF A SCENE RECOGNITION SYSTEM USING
NEURAL NETWORK MODELS |
| title_full | DESIGN AND DEVELOPMENT OF A SCENE RECOGNITION SYSTEM USING
NEURAL NETWORK MODELS |
| title_fullStr | DESIGN AND DEVELOPMENT OF A SCENE RECOGNITION SYSTEM USING
NEURAL NETWORK MODELS |
| title_full_unstemmed | DESIGN AND DEVELOPMENT OF A SCENE RECOGNITION SYSTEM USING
NEURAL NETWORK MODELS |
| title_short | DESIGN AND DEVELOPMENT OF A SCENE RECOGNITION SYSTEM USING
NEURAL NETWORK MODELS |
| title_sort | design and development of a scene recognition system using
neural network models |
| topic | H Social Sciences (General) QA76 Computer software |
| url | http://ir.unimas.my/id/eprint/32949/1/Ong%20Hui%20Xin%20-%2024%20pgs.pdf http://ir.unimas.my/id/eprint/32949/4/Ong%20Hui%20Xin%20ft.pdf http://ir.unimas.my/id/eprint/32949/ |
| url_provider | http://ir.unimas.my/ |