# Measurement of Disease Severity of Rice Crop Using Machine Learning and Computational Intelligence

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/measurement-of-disease-severity-of-rice-crop-using-machine-learning-and/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Prabira Kumar Sethy,Baishalee Negi,Nalini Kanta Barpanda,Santi Kumari Behera,Amiya Kumar Rath |
| Citations | 41 |
| DOI | 10.1007/978-981-10-6698-6_1 |
| Fields | Agricultural and Biological Sciences,Chemistry |
| Open Access | false |
| OA Status | closed |
| OpenAlex ID | https://openalex.org/W2776385595 |
| Type | book-chapter |
| Year | 2017 |

## Paper authors

- [Nalini Kanta Barpanda](https://scholariq.org/researchers/nalini-kanta-barpanda/)

## Paper primary topic

- [Smart Agriculture and AI](https://scholariq.org/topics/smart-agriculture-and-ai/)

## Paper topics

- [Smart Agriculture and AI](https://scholariq.org/topics/smart-agriculture-and-ai/)
- [Spectroscopy and Chemometric Analyses](https://scholariq.org/topics/spectroscopy-and-chemometric-analyses/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.