2022
DOI: 10.2352/j.imagingsci.technol.2022.66.5.050501
|View full text |Cite
|
Sign up to set email alerts
|

Multi-Scale Features Fusion Convolutional Neural Networks for Rice Leaf Disease Identification

Abstract: It is time-consuming and labor-intensive to detect rice diseases manually. The purpose of this research is to develop a convolutional neural networks (CNNs)-based system to automatically detect the diseased rice leaf infected with rice leaf blast, helminthosporium leaf blight, and bacterial leaf blight. The sizes of rice leaf spots vary with the severity of disease infection. A single model based CNN cannot effectively classify images, especially for images with objects of small size as well as multiple object… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

0
0
0

Year Published

2022
2022
2023
2023

Publication Types

Select...
2

Relationship

0
2

Authors

Journals

citations
Cited by 2 publications
references
References 37 publications
0
0
0
Order By: Relevance