Application of PSO in CNN attribute weighting for banana tree classification based on leaf images

Suamanda Ika Novichasari, Imam Adi Nata

Abstract


Banana (Musa paradisiaca) is a very popular fruit in Indonesia. Banana production in Indonesia, with more than 200 types of bananas, accounts for more than 50% of banana production in Asia. Differences in how to consume Ambon bananas and Kepok bananas and their various benefits encourage cultivators to be careful in choosing seeds to avoid mistakes. Distinguishing the seeds of Ambon bananas and kepok bananas is more difficult than distinguishing between Ambon bananas and kepok bananas. This is because the leaves and stems of the seeds look the same. The purpose of this study is to use an optimization algorithm to improve the performance of the image classification algorithm on the image of kepok banana leaves and Ambon bananas to assist in the selection of banana plant seeds that can be used by banana cultivators to get the maximum benefit according to the desired type of banana. The results of this study are used as the basis for making a decision support system to assist in the selection of banana plant seeds that can be used by banana cultivators in order to get the maximum benefit according to the desired type of banana

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DOI: https://doi.org/10.33633/jais.v8i3.9170

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Journal of Applied Intelligent System (e-ISSN : 2502-9401, p-ISSN : 2503-0493) is published by Department of Informatics Universitas Dian Nuswantoro Semarang and IndoCEISS.

  

 

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