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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.
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基于AlexNet的视频异常检测技术
异常检测
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文献信息
篇名 An Efficient Disease Detection Technique of Rice Leaf Using AlexNet
来源期刊 电脑和通信(英文) 学科 农学
关键词 AlexNet Leaf Diseases Disease Prediction Rice Leaf Disease Dataset Disease Classification
年,卷(期) 2020,(12) 所属期刊栏目
研究方向 页码范围 49-57
页数 9页 分类号 S51
字数 语种
DOI
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研究主题发展历程
节点文献
AlexNet
Leaf
Diseases
Disease
Prediction
Rice
Leaf
Disease
Dataset
Disease
Classification
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期刊影响力
电脑和通信(英文)
月刊
2327-5219
武汉市江夏区汤逊湖北路38号光谷总部空间
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783
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