کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
8959779 1646355 2018 7 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
A recognition method for cucumber diseases using leaf symptom images based on deep convolutional neural network
ترجمه فارسی عنوان
یک روش تشخیص بیماری های خیار با استفاده از تصاویر علامت برگ بر اساس شبکه عصبی کانولوشن عمیق است
کلمات کلیدی
خیار، بیماری ها، شبکه عصبی کانولوشن عمیق، علائم تصاویر، به رسمیت شناختن،
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر نرم افزارهای علوم کامپیوتر
چکیده انگلیسی
Manual approaches to recognize cucumber diseases are often time-consuming, laborious and subjective. A deep convolutional neural network (DCNN) was proposed to conduct symptom-wise recognition of four cucumber diseases, i.e., anthracnose, downy mildew, powdery mildew, and target leaf spots. The symptom images were segmented from cucumber leaf images captured under field conditions. In order to decrease the chance of overfitting, data augmentation methods were utilized to enlarge the datasets formed by the segmented symptom images. With the augmented datasets containing 14,208 symptom images, the DCNN achieved good recognition results, with an accuracy of 93.4%. In order to compare the results of the DCNN, comparative experiments were conducted using conventional classifiers (Random Forest and Support Vector Machines), as well as AlexNet. Results showed that the DCNN was a robust tool for recognizing the cucumber diseases in field conditions.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computers and Electronics in Agriculture - Volume 154, November 2018, Pages 18-24
نویسندگان
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