# Image-based Plant Disease Diagnosis with Unsupervised Anomaly Detection Based on Reconstructability of Colors

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/image-based-plant-disease-diagnosis-with-unsupervised-anomaly-detection-based-on/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Ryoya Katafuchi,T Tokunaga |
| Citations | 3 |
| DOI | 10.48550/arxiv.2011.14306 |
| Fields | Agricultural and Biological Sciences |
| Open Access | true |
| OA Status | green |
| OA URL | https://arxiv.org/pdf/2011.14306 |
| OpenAlex ID | https://openalex.org/W3107677640 |
| Type | preprint |
| Year | 2020 |

## Paper authors

- [Ryoya Katafuchi](https://scholariq.org/researchers/ryoya-katafuchi/)

## Paper journal

- [arXiv (Cornell University)](https://scholariq.org/journals/arxiv-cornell-university/)

## 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 Pathogenic Bacteria Studies](https://scholariq.org/topics/plant-pathogenic-bacteria-studies/)
- [Plant Virus Research Studies](https://scholariq.org/topics/plant-virus-research-studies/)

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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.