# Agricultural Pest Super-Resolution and Identification With Attention Enhanced Residual and Dense Fusion Generative and Adversarial Network

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/agricultural-pest-super-resolution-and-identification-with-attention-enhanced/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Qiang Dai,Xi Cheng,Yan Qiao,Youhua Zhang |
| Citations | 41 |
| DOI | 10.1109/access.2020.2991552 |
| Fields | Agricultural and Biological Sciences,Engineering,Environmental Science |
| Open Access | true |
| OA Status | gold |
| OA URL | https://ieeexplore.ieee.org/ielx7/6287639/8948470/09082695.pdf |
| OpenAlex ID | https://openalex.org/W3021425978 |
| Type | article |
| Year | 2020 |

## Paper authors

- [Yan Qiao](https://scholariq.org/researchers/yan-qiao/)

## Paper journal

- [IEEE Access](https://scholariq.org/journals/ieee-access/)

## 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/)
- [Image Processing Techniques and Applications](https://scholariq.org/topics/image-processing-techniques-and-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.