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: | English |
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Ijetea
2023
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| Subjects: | |
| Online Access: | http://eprints.uthm.edu.my/8899/ http://eprints.uthm.edu.my/8899/1/J15817_93d696d741ce66312d4270d55ad734db.pdf |
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| author | Yusof, Aiman Kamarudin, Noraziahtulhidayu Al-Emad, Nabil Ali Sapuan, Khusairi |
| author_facet | Yusof, Aiman Kamarudin, Noraziahtulhidayu Al-Emad, Nabil Ali Sapuan, Khusairi |
| author_sort | Yusof, Aiman |
| building | UTHM Institutional Repository |
| collection | Online Access |
| 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. |
| first_indexed | 2025-11-15T20:27:36Z |
| format | Article |
| id | uthm-8899 |
| institution | Universiti Tun Hussein Onn Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T20:27:36Z |
| publishDate | 2023 |
| publisher | Ijetea |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | uthm-88992023-06-18T01:34:09Z http://eprints.uthm.edu.my/8899/ Durian Farm Threats Identification through Convolution Neural Networks and Multimedia Mobile Development Yusof, Aiman Kamarudin, Noraziahtulhidayu Al-Emad, Nabil Ali Sapuan, Khusairi 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. Ijetea 2023 Article PeerReviewed text en http://eprints.uthm.edu.my/8899/1/J15817_93d696d741ce66312d4270d55ad734db.pdf Yusof, Aiman and Kamarudin, Noraziahtulhidayu and Al-Emad, Nabil Ali and Sapuan, Khusairi (2023) Durian Farm Threats Identification through Convolution Neural Networks and Multimedia Mobile Development. International Journal of Emerging Technology and Advanced Engineering, 13 (3). pp. 8-15. ISSN 2250-2459 https://doi.org/10.46338/ijetae0223_02 |
| spellingShingle | T Technology (General) Yusof, Aiman Kamarudin, Noraziahtulhidayu Al-Emad, Nabil Ali Sapuan, Khusairi 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/8899/ http://eprints.uthm.edu.my/8899/ http://eprints.uthm.edu.my/8899/1/J15817_93d696d741ce66312d4270d55ad734db.pdf |