Transfer Learning for Caladium bicolor Classification: Proof of Concept to Application Development

• Porawat Visutsak,
• Xiabi Liu,
• Keun Ho Ryu,
• Naphat Bussabong,
• Nicha Sirikong,
• Preeyaphorn Intamong,
• Warakorn Sonnui,
• Siriwan Boonkerd,
• Jirawat Thongpiem,
• Maythar Poonpanit,
• Akarasate Homwiseswongsa,
• Kittipot Hirunwannapong,
• Chaimongkol Suksomsong,
• Rittikait Budrit,

Vol. 18, No. 1, January 31, 2024
10.3837/tiis.2024.01.008, Download Paper (Free):

• Classification
• feature extraction
• Caladium bicolor
• Software development
• UX/UI concept.

Abstract

Caladium bicolor is one of the most popular plants in Thailand. The original species of Caladium bicolor was found a hundred years ago. Until now, there are more than 500 species through multiplication. The classification of Caladium bicolor can be done by using its color and shape. This study aims to develop a model to classify Caladium bicolor using a transfer learning technique. This work also presents a proof of concept, GUI design, and web application deployment using the user-design-center method. We also evaluated the performance of the following pre-trained models in this work, and the results are as follow: 87.29% for AlexNet, 90.68% for GoogleNet, 93.59% for XceptionNet, 93.22% for MobileNetV2, 89.83% for RestNet18, 88.98% for RestNet50, 97.46% for RestNet101, and 94.92% for InceptionResNetV2. This work was implemented using MATLAB R2023a.

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