# DDAN-RGAL: A Dual-Domain Adaptive Network With Reality-Gap Aware Learning for Field-Deployable Plant Disease Detection

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/ddan-rgal-a-dual-domain-adaptive-network-with-reality-gap-aware-learning-for/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Syed Asif Ahmad Qadri,Nen Fu Huang,Yu-Hsiang Huang,Pin-Cheng Chan |
| Citations | 0 |
| DOI | 10.1109/tafe.2026.3667568 |
| Fields | Agricultural and Biological Sciences,Computer Science |
| Open Access | false |
| OA Status | closed |
| OpenAlex ID | https://openalex.org/W7141671698 |
| Type | article |
| Year | 2026 |

## Paper authors

- [Syed Asif Ahmad Qadri](https://scholariq.org/researchers/syed-asif-ahmad-qadri/)
- [Nen Fu Huang](https://scholariq.org/researchers/nen-fu-huang/)
- [Pin-Cheng Chan](https://scholariq.org/researchers/pin-cheng-chan/)

## Paper journal

- [IEEE Transactions on AgriFood Electronics](https://scholariq.org/journals/ieee-transactions-on-agrifood-electronics/)

## 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/)
- [Advanced Neural Network Applications](https://scholariq.org/topics/advanced-neural-network-applications/)
- [Neural Networks and Reservoir Computing](https://scholariq.org/topics/neural-networks-and-reservoir-computing/)

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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.