# 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-2/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Ryoya Katafuchi,T Tokunaga |
| Citations | 12 |
| DOI | 10.5220/0010463201120120 |
| Fields | Agricultural and Biological Sciences |
| Open Access | true |
| OA Status | gold |
| OA URL | https://doi.org/10.5220/0010463201120120 |
| OpenAlex ID | https://openalex.org/W3159077752 |
| Type | conference-paper |
| Year | 2021 |

## Paper authors

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

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