# A meta-learning framework for recommending CNN models for plant disease identification tasks

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/a-meta-learning-framework-for-recommending-cnn-models-for-plant-disease/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Sahil Verma,Prabhat Kumar,Jyoti Prakash Singh |
| Citations | 30 |
| DOI | 10.1016/j.compag.2023.107708 |
| Fields | Agricultural and Biological Sciences |
| Open Access | false |
| OA Status | closed |
| OpenAlex ID | https://openalex.org/W4322632453 |
| Type | article |
| Year | 2023 |

## Paper authors

- [Sahil Verma](https://scholariq.org/researchers/sahil-verma/)
- [Prabhat Kumar](https://scholariq.org/researchers/prabhat-kumar/)
- [Jyoti Prakash Singh](https://scholariq.org/researchers/jyoti-prakash-singh/)

## Paper journal

- [Computers and Electronics in Agriculture](https://scholariq.org/journals/computers-and-electronics-in-agriculture/)

## 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/)
- [Plant Disease Management Techniques](https://scholariq.org/topics/plant-disease-management-techniques/)
- [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.