文章基本信息

标题：An Efficient Disease Detection Technique of Rice Leaf Using AlexNet
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作者：Md. Mafiul Hasan Matin ; Amina Khatun ; Md. Golam Moazzam 等
期刊名称：Journal of Computer and Communications
印刷版ISSN：2327-5219
电子版ISSN：2327-5227
出版年度：2020
卷号：08
期号：12
页码：49-57
DOI：10.4236/jcc.2020.812005
语种：English
出版社：Scientific Research Publishing
摘要：As nearly half of the people in the world live on rice, so the rice leaf disease detection is very important for our agricultural sector. Many researchers worked on this problem and they achieved different results according to their applied techniques. In this paper, we applied AlexNet technique to detect the three prevalence rice leaf diseases termed as bacterial blight, brown spot as well as leaf smut and got a remarkable outcome rather than the previous works. AlexNet is a special type of classification technique of deep learning. This paper shows more than 99% accuracy due to adjusting an efficient technique and image augmentation.
关键词：AlexNet;Leaf Diseases;Disease Prediction;Rice Leaf Disease Dataset;Disease Classification