# Automated identification of tomato leaf pathologies using deep learning via ResNet18 and a Tailored CNN Architecture

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/automated-identification-of-tomato-leaf-pathologies-using-deep-learning-via/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Yanto Supriyanto |
| Citations | 0 |
| DOI | 10.37373/tekno.v13i1.1762 |
| Fields | Agricultural and Biological Sciences,Computer Science |
| Open Access | true |
| OA Status | diamond |
| OA URL | https://jurnal.sttmcileungsi.ac.id/index.php/tekno/article/download/1762/830 |
| OpenAlex ID | https://openalex.org/W7129107238 |
| Type | article |
| Year | 2026 |

## Paper authors

- [Yanto Supriyanto](https://scholariq.org/researchers/yanto-supriyanto/)

## Paper journal

- [TEKNOSAINS Jurnal Sains Teknologi dan Informatika](https://scholariq.org/journals/teknosains-jurnal-sains-teknologi-dan-informatika/)

## 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/)
- [Plant Disease Management Techniques](https://scholariq.org/topics/plant-disease-management-techniques/)
- [Advanced Neural Network Applications](https://scholariq.org/topics/advanced-neural-network-applications/)

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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.