# LT-YOLOv10n: A lightweight IoT-integrated deep learning model for real-time tomato leaf disease detection and management

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/lt-yolov10n-a-lightweight-iot-integrated-deep-learning-model-for-real-time/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Abdelaaziz Bellout,Mohamed Zarboubi,Mohamed Elhoseny,Azzedine Dliou,Rachid Latif,Amine Saddik |
| Citations | 18 |
| DOI | 10.1016/j.iot.2025.101663 |
| Fields | Agricultural and Biological Sciences,Environmental Science |
| Open Access | false |
| OA Status | closed |
| OpenAlex ID | https://openalex.org/W4411306378 |
| Type | article |
| Year | 2025 |

## Paper authors

- [Abdelaaziz Bellout](https://scholariq.org/researchers/abdelaaziz-bellout/)
- [Azzedine Dliou](https://scholariq.org/researchers/azzedine-dliou/)
- [Amine Saddik](https://scholariq.org/researchers/amine-saddik/)

## 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/)
- [Remote Sensing in Agriculture](https://scholariq.org/topics/remote-sensing-in-agriculture/)
- [Greenhouse Technology and Climate Control](https://scholariq.org/topics/greenhouse-technology-and-climate-control/)

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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.