# A Cutting-Edge Machine Learning Framework for Potato Leaf Disease Detection

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/a-cutting-edge-machine-learning-framework-for-potato-leaf-disease-detection/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Manoj Kumar,Urmila Pilania,Aayush Kumar Singh,Tanishk Tanishk,Naveen Gill,Aditya Nagar |
| Citations | 3 |
| DOI | 10.1109/icdt63985.2025.10986555 |
| Fields | Agricultural and Biological Sciences,Chemistry |
| Open Access | false |
| OA Status | closed |
| OpenAlex ID | https://openalex.org/W4410342163 |
| Type | conference-paper |
| Year | 2025 |

## Paper authors

- [Urmila Pilania](https://scholariq.org/researchers/urmila-pilania/)
- [Tanishk Tanishk](https://scholariq.org/researchers/tanishk-tanishk/)
- [Naveen Gill](https://scholariq.org/researchers/naveen-gill/)
- [Aditya Nagar](https://scholariq.org/researchers/aditya-nagar/)

## 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/)
- [Leaf Properties and Growth Measurement](https://scholariq.org/topics/leaf-properties-and-growth-measurement/)

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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.