Performance and Applicability of Transfer Learners for Cocoa Swollen Shoot Detection

Justice Kwame Appati
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Justice Kwame Appati: University of Ghana, Ghana

International Journal of Technology Diffusion (IJTD), 2021, vol. 12, issue 2, 68-77

Abstract: An accurate and reliable cocoa swollen shoot disease diagnosis is the desire of traditional farmers with low-resolution smart devices. In this study, an efficient cocoa swollen shoot disease identification method base on transfer learners using pre-trained VGG16 and ResNet was proposed. These pre-trained models were trained using 456 samples and validated with 114 samples. The dataset constitutes low-resolution images, VGG16 and ResNet, and achieved an accuracy of 98.25 and 94.73%, respectively. With the objective of proposing a more reliable and accurate model, VGG16 is noted to scale better in terms of performance for implementation.

Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:igg:jtd000:v:12:y:2021:i:2:p:68-77

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