# Resource-efficient federated learning over IoAT for rice leaf disease classification

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/resource-efficient-federated-learning-over-ioat-for-rice-leaf-disease/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Meenakshi Aggarwal,Vikas Khullar,Nitin Goyal,Thomas André Prola |
| Citations | 55 |
| DOI | 10.1016/j.compag.2024.109001 |
| Fields | Agricultural and Biological Sciences,Computer Science,Environmental Science |
| Open Access | false |
| OA Status | closed |
| OpenAlex ID | https://openalex.org/W4396684696 |
| Type | article |
| Year | 2024 |

## Paper authors

- [Meenakshi Aggarwal](https://scholariq.org/researchers/meenakshi-aggarwal/)
- [Vikas Khullar](https://scholariq.org/researchers/vikas-khullar/)
- [Nitin Goyal](https://scholariq.org/researchers/nitin-goyal/)
- [Thomas André Prola](https://scholariq.org/researchers/thomas-andre-prola/)

## 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/)
- [Water Quality Monitoring Technologies](https://scholariq.org/topics/water-quality-monitoring-technologies/)
- [IoT and Edge/Fog Computing](https://scholariq.org/topics/iot-and-edge-fog-computing/)

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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.