# Non-Destructive Detection of Soybean Pest Based on Hyperspectral Image and Attention-ResNet Meta-Learning Model

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/non-destructive-detection-of-soybean-pest-based-on-hyperspectral-image-and/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Jiangsheng Gui,Huirong Xu,Jingyi Fei |
| Citations | 14 |
| DOI | 10.3390/s23020678 |
| Fields | Agricultural and Biological Sciences,Chemistry,Engineering |
| Open Access | true |
| OA Status | gold |
| OA URL | https://www.mdpi.com/1424-8220/23/2/678/pdf?version=1673518322 |
| OpenAlex ID | https://openalex.org/W4313889779 |
| PMID | 36679470 |
| Type | article |
| Year | 2023 |

## Paper authors

- [Jiangsheng Gui](https://scholariq.org/researchers/jiangsheng-gui/)

## Paper journal

- [Sensors](https://scholariq.org/journals/sensors/)

## Paper primary topic

- [Spectroscopy and Chemometric Analyses](https://scholariq.org/topics/spectroscopy-and-chemometric-analyses/)

## Paper topics

- [Spectroscopy and Chemometric Analyses](https://scholariq.org/topics/spectroscopy-and-chemometric-analyses/)
- [Smart Agriculture and AI](https://scholariq.org/topics/smart-agriculture-and-ai/)
- [Advanced Chemical Sensor Technologies](https://scholariq.org/topics/advanced-chemical-sensor-technologies/)

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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.