# Automated Paddy Leaf Disease Identification using Visual Leaf Images based on Nine Pre-trained Models Approach

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/automated-paddy-leaf-disease-identification-using-visual-leaf-images-based-on/

## Facts

| Field | Value |
| --- | --- |
| Author Names | A Petchiammal,D. Murugan |
| Citations | 9 |
| DOI | 10.1016/j.procs.2024.12.013 |
| Fields | Agricultural and Biological Sciences,Environmental Science |
| Open Access | true |
| OA Status | diamond |
| OA URL | https://doi.org/10.1016/j.procs.2024.12.013 |
| OpenAlex ID | https://openalex.org/W4407301705 |
| Type | conference-paper |
| Year | 2025 |

## Paper authors

- [A Petchiammal](https://scholariq.org/researchers/a-petchiammal/)
- [D. Murugan](https://scholariq.org/researchers/d-murugan/)

## Paper journal

- [Procedia Computer Science](https://scholariq.org/journals/procedia-computer-science/)

## 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/)
- [Leaf Properties and Growth Measurement](https://scholariq.org/topics/leaf-properties-and-growth-measurement/)
- [Remote Sensing in Agriculture](https://scholariq.org/topics/remote-sensing-in-agriculture/)

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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.