Classification of Mango Leaf Disease using Machine Learning to Enhance Yield Productivity

被引:0
作者
Joshi, Deepali [1 ]
Patil, Harshali [1 ]
Bendre, Varsha [2 ]
Katti, Jayashree [3 ]
机构
[1] Thakur Coll Engn & Technol, Dept Comp Engn, Mumbai, Maharashtra, India
[2] Pimpri Chinchwad Coll Engn, Dept E&TC, Pune, Maharashtra, India
[3] Pimpri Chinchwad Coll Engn, Dept Informat Technol, Pune, Maharashtra, India
关键词
Mango; Mango Leaves; Mango disease; Production; ANN; KNN; Machine Learning; NEURAL-NETWORK;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Fruits provide critical nourishment to the human body. Proper Care and upkeep are essential for the fruit to be healthy. Lack of maintenance, infections, spot, fungus all cause significant production and profit losses. Mango is a seasonal and famous fruit which is consumed all over the world. It is a delicate fruit that is susceptible to disease that reduce the quality as well as quantity. Manual illness or infection inspection is a time-consuming and labour-intensive technique that necessitates a large amount of resources and therefore it is inefficient. On the other hand, automatic inspection provides various advantages such as less time consuming, less labour and also the number of resources required are less. Image classification techniques and algorithms can be used to distinguish between infected and healthy mangoes, decreasing losses.
引用
收藏
页码:348 / 357
页数:10
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