Rice Leaf Diseases Identify Using Big Transfer

Anurak Yutthanawa, Janya Onpans
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Abstract

In Thailand and numerous other Southeast Asian countries, Rice is one of the most income country products. Rice leaf disease control must be improved in order to enhance rice production. But it is a complicated process dependent on the farmer's experience and local knowledge. Artificial intelligence solutions will become one of the options for resolving this problem and informing all new and existing farmers about the diseases of their products. Big Transfer (BiT) is a deep learning model proposed in this paper for identifying rice leaf disease. BiT-M prediction performance is notable, with 100% prediction accuracy after 19 epochs of training.
利用大移栽技术鉴定水稻叶片病害
在泰国和许多其他东南亚国家,大米是收入最高的国家产品之一。为了提高水稻产量,必须加强水稻叶病防治。但这是一个复杂的过程,取决于农民的经验和当地知识。人工智能解决方案将成为解决这一问题的选择之一,并向所有新的和现有的农民通报他们产品的疾病。大转移(BiT)是本文提出的一种用于水稻叶片病害识别的深度学习模型。BiT-M预测性能显著,经过19次训练,预测准确率达到100%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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