# Application of extreme learning machine in plant disease prediction for highly imbalanced dataset

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/application-of-extreme-learning-machine-in-plant-disease-prediction-for-highly/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Anshul Bhatia,Anuradha Chug,Amit Prakash Singh |
| Citations | 58 |
| DOI | 10.1080/09720510.2020.1799504 |
| Fields | Agricultural and Biological Sciences,Computer Science |
| Open Access | false |
| OA Status | closed |
| OpenAlex ID | https://openalex.org/W3080596635 |
| Type | article |
| Year | 2020 |

## Paper authors

- [Anuradha Chug](https://scholariq.org/researchers/anuradha-chug/)
- [Amit Prakash Singh](https://scholariq.org/researchers/amit-prakash-singh/)

## 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/)
- [Machine Learning and ELM](https://scholariq.org/topics/machine-learning-and-elm/)
- [Plant Virus Research Studies](https://scholariq.org/topics/plant-virus-research-studies/)

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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.