# Shiva Mehta

**Type:** Researchers  
**Canonical URL:** https://scholariq.org/researchers/shiva-mehta/

## Facts

| Field | Value |
| --- | --- |
| Citations | 2,932 |
| Field | Smart Agriculture and AI |
| h-index | 26 |
| i10-index | 57 |
| Last Known Institution | Chitkara University |
| OpenAlex ID | https://openalex.org/A5061558029 |
| ORCID iD | 0009-0002-5537-7027 |
| Works | 385 |

## Researcher papers

- [Revolutionizing Maize Disease Management with Federated Learning CNNs: A Decentralized and Privacy-Sensitive Approach](https://scholariq.org/papers/revolutionizing-maize-disease-management-with-federated-learning-cnns-a/)
- [Empowering Farmers with AI: Federated Learning of CNNs for Wheat Diseases Multi-Classification](https://scholariq.org/papers/empowering-farmers-with-ai-federated-learning-of-cnns-for-wheat-diseases-multi/)
- [Improving Crop Health Management: Federated Learning CNN for Spinach Leaf Disease Detection](https://scholariq.org/papers/improving-crop-health-management-federated-learning-cnn-for-spinach-leaf-disease/)
- [Advanced Mango Leaf Disease Detection and Severity Analysis with Federated Learning and CNN](https://scholariq.org/papers/advanced-mango-leaf-disease-detection-and-severity-analysis-with-federated/)
- [A Federated Learning CNN Approach for Tomato Leaf Disease with Severity Analysis](https://scholariq.org/papers/a-federated-learning-cnn-approach-for-tomato-leaf-disease-with-severity-analysis/)
- [Transforming Agriculture : Federated Learning CNNs for Wheat Disease Severity Assessment](https://scholariq.org/papers/transforming-agriculture-federated-learning-cnns-for-wheat-disease-severity/)
- [Next-Generation Wheat Disease Monitoring: Leveraging Federated Convolutional Neural Networks for Severity Estimation](https://scholariq.org/papers/next-generation-wheat-disease-monitoring-leveraging-federated-convolutional/)
- [Exploring the Potential of Convolutional Neural Networks in Automatic Diagnosis of Dragon Fruit Diseases from Plant Photographs](https://scholariq.org/papers/exploring-the-potential-of-convolutional-neural-networks-in-automatic-diagnosis/)
- [Advancing Agricultural Practices: Federated Learning-based CNN for Mango Leaf Disease Detection](https://scholariq.org/papers/advancing-agricultural-practices-federated-learning-based-cnn-for-mango-leaf/)
- [Empowering Precision Agriculture: Detecting Apple Leaf Diseases and Severity Levels with Federated Learning CNN](https://scholariq.org/papers/empowering-precision-agriculture-detecting-apple-leaf-diseases-and-severity/)
- [Tackling Agricultural Challenges of Red Globe Grapes Leaf Diseases: A Federated Learning CNN Approach](https://scholariq.org/papers/tackling-agricultural-challenges-of-red-globe-grapes-leaf-diseases-a-federated/)
- [Enhancing Soybean Disease Diagnosis using CNN-based Feature Extraction and Random Forest Classification](https://scholariq.org/papers/enhancing-soybean-disease-diagnosis-using-cnn-based-feature-extraction-and/)

## Researcher 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/)
- [Brain Tumor Detection and Classification](https://scholariq.org/topics/brain-tumor-detection-and-classification/)
- [Smart Systems and Machine Learning](https://scholariq.org/topics/smart-systems-and-machine-learning/)
- [Date Palm Research Studies](https://scholariq.org/topics/date-palm-research-studies/)

## Researcher university

- [Chitkara University](https://scholariq.org/institutions/chitkara-university/)

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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.