Durian Farm Threats Identification through Convolution Neural Networks and Multimedia Mobile Development
The difficulties to drive away the durian farm threatens animals such as wild boars, monkeys, foxes, and squirrels during nighttime often experienced by durian farmers. Therefore, the Pro Durian application is proposed that allows farmers to identify durian threats through a camera phone with an ale...
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| Format: | Article |
| Language: | en |
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IJATAE
2023
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| Online Access: | http://eprints.uthm.edu.my/10450/1/J15817_93d696d741ce66312d4270d55ad734db.pdf http://eprints.uthm.edu.my/10450/ https://doi.org/10.46338/ijetae0223_02 |
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| author | Aiman Yusof, Aiman Yusof Kamarudin, Noraziahtulhidayu Nabil Ali Al-Emad, Nabil Ali Al-Emad Khusairi Sapuan, Khusairi Sapuan |
| author_facet | Aiman Yusof, Aiman Yusof Kamarudin, Noraziahtulhidayu Nabil Ali Al-Emad, Nabil Ali Al-Emad Khusairi Sapuan, Khusairi Sapuan |
| author_sort | Aiman Yusof, Aiman Yusof |
| building | UTHM Library |
| collection | Institutional Repository |
| content_provider | Universiti Tun Hussein Onn Malaysia |
| content_source | UTHM Institutional Repository |
| continent | Asia |
| country | Malaysia |
| description | The difficulties to drive away the durian farm threatens animals such as wild boars, monkeys, foxes, and squirrels during nighttime often experienced by durian farmers. Therefore, the Pro Durian application is proposed that allows farmers to identify durian threats through a camera phone with an alert feature activation when the system detects an animal to drive away those animals. The application implements a deep learning algorithm of Convolutional Neural Network (CNN)-YOLO3in order to receive the best output results in identifying the different datasets of durian farm threats. The classification accuracies reached 80% in detecting the animal’s images. |
| format | Article |
| id | my.uthm.eprints-10450 |
| institution | Universiti Tun Hussein Onn Malaysia |
| language | en |
| publishDate | 2023 |
| publisher | IJATAE |
| record_format | eprints |
| spelling | my.uthm.eprints-104502023-11-21T01:48:02Z http://eprints.uthm.edu.my/10450/ Durian Farm Threats Identification through Convolution Neural Networks and Multimedia Mobile Development Aiman Yusof, Aiman Yusof Kamarudin, Noraziahtulhidayu Nabil Ali Al-Emad, Nabil Ali Al-Emad Khusairi Sapuan, Khusairi Sapuan T Technology (General) The difficulties to drive away the durian farm threatens animals such as wild boars, monkeys, foxes, and squirrels during nighttime often experienced by durian farmers. Therefore, the Pro Durian application is proposed that allows farmers to identify durian threats through a camera phone with an alert feature activation when the system detects an animal to drive away those animals. The application implements a deep learning algorithm of Convolutional Neural Network (CNN)-YOLO3in order to receive the best output results in identifying the different datasets of durian farm threats. The classification accuracies reached 80% in detecting the animal’s images. IJATAE 2023 Article PeerReviewed text en http://eprints.uthm.edu.my/10450/1/J15817_93d696d741ce66312d4270d55ad734db.pdf Aiman Yusof, Aiman Yusof and Kamarudin, Noraziahtulhidayu and Nabil Ali Al-Emad, Nabil Ali Al-Emad and Khusairi Sapuan, Khusairi Sapuan (2023) Durian Farm Threats Identification through Convolution Neural Networks and Multimedia Mobile Development. International Journal of Emerging Technology and Advanced Engineering, 13 (2). pp. 8-15. ISSN 2250-2459 https://doi.org/10.46338/ijetae0223_02 |
| spellingShingle | T Technology (General) Aiman Yusof, Aiman Yusof Kamarudin, Noraziahtulhidayu Nabil Ali Al-Emad, Nabil Ali Al-Emad Khusairi Sapuan, Khusairi Sapuan Durian Farm Threats Identification through Convolution Neural Networks and Multimedia Mobile Development |
| title | Durian Farm Threats Identification through Convolution Neural
Networks and Multimedia Mobile Development |
| title_full | Durian Farm Threats Identification through Convolution Neural
Networks and Multimedia Mobile Development |
| title_fullStr | Durian Farm Threats Identification through Convolution Neural
Networks and Multimedia Mobile Development |
| title_full_unstemmed | Durian Farm Threats Identification through Convolution Neural
Networks and Multimedia Mobile Development |
| title_short | Durian Farm Threats Identification through Convolution Neural
Networks and Multimedia Mobile Development |
| title_sort | durian farm threats identification through convolution neural
networks and multimedia mobile development |
| topic | T Technology (General) |
| url | http://eprints.uthm.edu.my/10450/1/J15817_93d696d741ce66312d4270d55ad734db.pdf http://eprints.uthm.edu.my/10450/ https://doi.org/10.46338/ijetae0223_02 |
| url_provider | http://eprints.uthm.edu.my/ |