Citation

Mohd Derafi, Muhammad Izzat Faiz and Abdul Razak, Siti Fatimah and Sayeed, Md. Shohel (2024) Banana Disease Classification Using Transfer Learning. In: 2024 IEEE Symposium on Industrial Electronics & Applications (ISIEA), 6-7 July 2024, Kuala Lumpur, Malaysia.

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Abstract

The cultivation of bananas, which is a crucial aspect of world agriculture, has significant challenges due to numerous illnesses that pose a threat to both the quantity and quality of the crop. The integration of artificial intelligence (AI) with agricultural sciences has brought about a significant change in recent years, providing advanced tools for the identification and assessment of diseases.This paper demonstrates the integration of transfer learning in banana disease classification which is scalable, unbiased, and prompt method. Pre-trained models including EfficientNet, AlexNet, VGG and ResNet have been experimented to classify 25 types of banana diseases based on three public datasets. The results revealed that VGG-19 with SGD optimizer is superior compared to other pre-trained models for this task

Item Type:	Conference or Workshop Item (Paper)
Uncontrolled Keywords:	agriculture, AI
Subjects:	Q Science > Q Science (General) > Q300-390 Cybernetics S Agriculture > SB Plant culture
Divisions:	Faculty of Information Science and Technology (FIST)
Depositing User:	Ms Nurul Iqtiani Ahmad
Date Deposited:	02 Sep 2024 07:04
Last Modified:	02 Sep 2024 07:04
URII:	http://shdl.mmu.edu.my/id/eprint/12903

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