# Diagnosis of contrast improved common maize leaf diseases using U2Net based deep learning model

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/diagnosis-of-contrast-improved-common-maize-leaf-diseases-using-u2net-based-deep/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Sunil Bhardwaj,Meenakashi Sood,Amod Kumar |
| Citations | 2 |
| DOI | 10.1016/j.procs.2025.04.301 |
| Fields | Agricultural and Biological Sciences,Chemistry,Computer Science |
| Open Access | true |
| OA Status | diamond |
| OA URL | https://doi.org/10.1016/j.procs.2025.04.301 |
| OpenAlex ID | https://openalex.org/W4410253104 |
| Type | conference-paper |
| Year | 2025 |

## Paper authors

- [Sunil Bhardwaj](https://scholariq.org/researchers/sunil-bhardwaj/)
- [Amod Kumar](https://scholariq.org/researchers/amod-kumar/)

## 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/)
- [Spectroscopy and Chemometric Analyses](https://scholariq.org/topics/spectroscopy-and-chemometric-analyses/)
- [Smart Systems and Machine Learning](https://scholariq.org/topics/smart-systems-and-machine-learning/)

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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.