Citation

Lee, Chee Cheong and Koo, Voon Chet and Lim, Tien Sze (2022) Oil Palm Tree Counting And Disease Detection Using Deep Neural Network. In: 2nd FET PG Engineering Colloquium Proceedings 2022, 1-15 December 2022, Multimedia University, Malaysia. (Unpublished)

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Abstract

Palm oil is among the most important agricultural commodities in Malaysia and contributes significantly to the to the economy. Estimated 4.5 million hectares of land occupied for palm oil cultivation and this make Malaysia one of the largest palm oil exporter in the world. One of the key information for plantation management is to know the number of oil palm trees and their location. This information helps to predict yield of palm oil, density of plantation area. Apart from number of trees, oil palm tree disease status is also important for plantation manager. Basel stem rot (BSR) cause by Ganoderma boninense result the most severe problem in oil palm plantation. Effective BSR disease detection is crucial to ensure stable palm oil production.

Item Type:	Conference or Workshop Item (Other)
Uncontrolled Keywords:	Neural networks (Computer science)
Subjects:	Q Science > QA Mathematics > QA71-90 Instruments and machines
Divisions:	Faculty of Engineering and Technology (FET)
Depositing User:	Ms Nurul Iqtiani Ahmad
Date Deposited:	16 Feb 2023 07:47
Last Modified:	16 Feb 2023 07:47
URII:	http://shdl.mmu.edu.my/id/eprint/10855

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