Evaluation of image processing technique in identifying rice blast disease in field conditions based on KNN algorithm improvement by K‐means-Reference-Cited by-同舟云学术

Evaluation of image processing technique in identifying rice blast disease in field conditions based on KNN algorithm improvement by K‐means

Published:2019-11-07 Issue:12 Volume:7 Page:3922-3930
ISSN:2048-7177
Container-title:Food Science & Nutrition
language:en
Short-container-title:Food Sci Nutr

Author:

Larijani Mohammad Reza¹,Asli‐Ardeh Ezzatollah Askari¹^ORCID,Kozegar Ehsan²,Loni Reyhaneh³

Affiliation:

1. Department of Biosystems Engineering University of Mohaghegh Ardabili Ardabil Iran

2. Department of Computer Sciences and Engineering University of Guilan Guilan Iran

3. Department of Biosystem Engineering Tarbiat Modares University Tehran Iran

Publisher

Wiley

Subject

Food Science

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/fsn3.1251

Reference20 articles.

1. Study of genetic diversity and important correlations of agronomic traits in rice genotypes (Oryza sativa L.);Agahi K.;Iranian Journal of Biology,2012

2. Detection and Classification of Leaf Diseases using K-means-based Segmentation and Neural-networks-based Classification

3. A Robust Recognition System for Pecan Weevil using Artificial Neural Networks

4. Molecular progress on the mapping and cloning of functional genes for blast disease in rice (Oryza sativaL.): current status and future considerations

5. Developing an orientation and cutting point determination algorithm for a trout fish processing system using machine vision

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