Research in Agricultural Engineering - Online first

A novel ensemble convolutional neural networksfor rice disease identificationOriginal Paper

Richard Alvin Pratama, Nabila Husna Shabrina

Res. Agr. Eng., X:X | DOI: 10.17221/59/2024-RAE  

Rice is a crucial food commodity worldwide, particularly in Asian countries. However, various factors, such as drought, floods, and pest attacks, can lead to the emergence of diseases in rice plants. Accurately identifying these diseases poses a significant challenge for farmers, often leading to significant yield losses. Conventionally, farmers rely on manual methods based on their experience and visual inspections to identify rice diseases. However, this approach is highly ineffective, time-consuming, and prone to error. This study aimed to address this issue by proposing advanced deep learning techniques, an ensemble learning method, to automate...