# Semi-supervised few-shot learning approach for plant diseases recognition

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/semi-supervised-few-shot-learning-approach-for-plant-diseases-recognition/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Yang Li,Xuewei Chao |
| Citations | 160 |
| DOI | 10.1186/s13007-021-00770-1 |
| Fields | Agricultural and Biological Sciences,Computer Science,Engineering |
| Open Access | true |
| OA Status | gold |
| OA URL | https://plantmethods.biomedcentral.com/track/pdf/10.1186/s13007-021-00770-1 |
| OpenAlex ID | https://openalex.org/W3175496851 |
| PMID | 34176505 |
| Type | article |
| Year | 2021 |

## Paper authors

- [Yang Li](https://scholariq.org/researchers/yang-li/)
- [Xuewei Chao](https://scholariq.org/researchers/xuewei-chao/)

## Paper journal

- [Plant Methods](https://scholariq.org/journals/plant-methods/)

## 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/)
- [Advanced Data and IoT Technologies](https://scholariq.org/topics/advanced-data-and-iot-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.