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Using Deep Convolutional Neural Networks for Image-Based Diagnosis of Nutrient Deficiencies in Rice
المؤلفون المشاركون
Guo, Xi
Xu, Zhe
Zhu, Anfan
He, Xiaolin
Zhao, Xiaomin
Subedi, Roshan
Han, Yi
المصدر
Computational Intelligence and Neuroscience
العدد
المجلد 2020، العدد 2020 (31 ديسمبر/كانون الأول 2020)، ص ص. 1-12، 12ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2020-08-28
دولة النشر
مصر
عدد الصفحات
12
التخصصات الرئيسية
الملخص EN
Symptoms of nutrient deficiencies in rice plants often appear on the leaves.
The leaf color and shape, therefore, can be used to diagnose nutrient deficiencies in rice.
Image classification is an efficient and fast approach for this diagnosis task.
Deep convolutional neural networks (DCNNs) have been proven to be effective in image classification, but their use to identify nutrient deficiencies in rice has received little attention.
In the present study, we explore the accuracy of different DCNNs for diagnosis of nutrient deficiencies in rice.
A total of 1818 photographs of plant leaves were obtained via hydroponic experiments to cover full nutrition and 10 classes of nutrient deficiencies.
The photographs were divided into training, validation, and test sets in a 3 : 1 : 1 ratio.
Fine-tuning was performed to evaluate four state-of-the-art DCNNs: Inception-v3, ResNet with 50 layers, NasNet-Large, and DenseNet with 121 layers.
All the DCNNs obtained validation and test accuracies of over 90%, with DenseNet121 performing best (validation accuracy = 98.62 ± 0.57%; test accuracy = 97.44 ± 0.57%).
The performance of the DCNNs was validated by comparison to color feature with support vector machine and histogram of oriented gradient with support vector machine.
This study demonstrates that DCNNs provide an effective approach to diagnose nutrient deficiencies in rice.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Xu, Zhe& Guo, Xi& Zhu, Anfan& He, Xiaolin& Zhao, Xiaomin& Han, Yi…[et al.]. 2020. Using Deep Convolutional Neural Networks for Image-Based Diagnosis of Nutrient Deficiencies in Rice. Computational Intelligence and Neuroscience،Vol. 2020, no. 2020, pp.1-12.
https://search.emarefa.net/detail/BIM-1138808
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Xu, Zhe…[et al.]. Using Deep Convolutional Neural Networks for Image-Based Diagnosis of Nutrient Deficiencies in Rice. Computational Intelligence and Neuroscience No. 2020 (2020), pp.1-12.
https://search.emarefa.net/detail/BIM-1138808
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Xu, Zhe& Guo, Xi& Zhu, Anfan& He, Xiaolin& Zhao, Xiaomin& Han, Yi…[et al.]. Using Deep Convolutional Neural Networks for Image-Based Diagnosis of Nutrient Deficiencies in Rice. Computational Intelligence and Neuroscience. 2020. Vol. 2020, no. 2020, pp.1-12.
https://search.emarefa.net/detail/BIM-1138808
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1138808
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
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