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/10251/1/J15817_93d696d741ce66312d4270d55ad734db.pdf http://eprints.uthm.edu.my/10251/ https://doi.org/10.46338/ijetae0223_02 |
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| author | Aiman Yusoff, Aiman Yusoff Noraziahtulhidayu Kamarudin, Noraziahtulhidayu Kamarudin Nabil Ali Al-Emad, Nabil Ali Al-Emad Khusairi Sapuan, Khusairi Sapuan |
| author_facet | Aiman Yusoff, Aiman Yusoff Noraziahtulhidayu Kamarudin, Noraziahtulhidayu Kamarudin Nabil Ali Al-Emad, Nabil Ali Al-Emad Khusairi Sapuan, Khusairi Sapuan |
| author_sort | Aiman Yusoff, Aiman Yusoff |
| 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-10251 |
| institution | Universiti Tun Hussein Onn Malaysia |
| language | en |
| publishDate | 2023 |
| publisher | IJATAE |
| record_format | eprints |
| spelling | my.uthm.eprints-102512023-10-25T07:27:27Z http://eprints.uthm.edu.my/10251/ Durian Farm Threats Identification through Convolution Neural Networks and Multimedia Mobile Development Aiman Yusoff, Aiman Yusoff Noraziahtulhidayu Kamarudin, Noraziahtulhidayu Kamarudin Nabil Ali Al-Emad, Nabil Ali Al-Emad Khusairi Sapuan, Khusairi Sapuan TJ210.2-211.47 Mechanical devices and figures. Automata. Ingenious mechanisms. Robots (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/10251/1/J15817_93d696d741ce66312d4270d55ad734db.pdf Aiman Yusoff, Aiman Yusoff and Noraziahtulhidayu Kamarudin, Noraziahtulhidayu Kamarudin 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 | TJ210.2-211.47 Mechanical devices and figures. Automata. Ingenious mechanisms. Robots (General) Aiman Yusoff, Aiman Yusoff Noraziahtulhidayu Kamarudin, Noraziahtulhidayu Kamarudin 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 | TJ210.2-211.47 Mechanical devices and figures. Automata. Ingenious mechanisms. Robots (General) |
| url | http://eprints.uthm.edu.my/10251/1/J15817_93d696d741ce66312d4270d55ad734db.pdf http://eprints.uthm.edu.my/10251/ https://doi.org/10.46338/ijetae0223_02 |
| url_provider | http://eprints.uthm.edu.my/ |