Khamis, Nurulaqilla and Selamat, Hazlina and Ghazalli, Shuwaibatul Aslamiah and Md. Saleh, Nurul Izrin and Yusoff, Nooraini (2022) Comparison of palm oil Fresh Fruit Bunches (FFB) ripeness classification technique using deep learning method. In: 13th Asian Control Conference, ASCC 2022, 4 - 7 May 2022, Jeju, South Korea.
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Official URL: http://dx.doi.org/10.23919/ASCC56756.2022.9828345
Abstract
The ripeness of palm oil fruit is currently determined through manual visual inspection by palm oil estate workers that could result inconsistent and inaccurate fruit grading. Moreover, the manual inspection is time-consuming and exhausting duty for humans to complete the daily repetitive task. To overcome this issue, this paper proposes an automatic fruit grading classification by utilizing computer vision technologies. A comparison using image classification (ResNet50) and object detection (YOLOv3) technique is analysed in this work. It is clearly demonstrated that object detection model is remarkable in improving ripeness category based on the finer level of feature that has been extracted during the convolutional process.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Uncontrolled Keywords: | Classification, Deep Learning, Palm Oil Fresh Bunches Ripeness, ResNet50, YOLOv3 |
| Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering |
| Divisions: | Electrical Engineering |
| ID Code: | 98624 |
| Deposited By: | Widya Wahid |
| Deposited On: | 25 Jan 2023 09:40 |
| Last Modified: | 25 Jan 2023 09:40 |
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