# T-CNN: Trilinear convolutional neural networks model for visual detection of plant diseases

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/t-cnn-trilinear-convolutional-neural-networks-model-for-visual-detection-of/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Dongfang Wang,Jun Wang,Wenrui Li,Ping Guan |
| Citations | 87 |
| DOI | 10.1016/j.compag.2021.106468 |
| Fields | Agricultural and Biological Sciences |
| Open Access | false |
| OA Status | closed |
| OpenAlex ID | https://openalex.org/W3202844853 |
| Type | article |
| Year | 2021 |

## Paper authors

- [Dongfang Wang](https://scholariq.org/researchers/dongfang-wang/)
- [Wenrui Li](https://scholariq.org/researchers/wenrui-li/)
- [Jun Wang](https://scholariq.org/researchers/jun-wang-2/)
- [Ping Guan](https://scholariq.org/researchers/ping-guan/)

## Paper journal

- [Computers and Electronics in Agriculture](https://scholariq.org/journals/computers-and-electronics-in-agriculture/)

## 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 Disease Management Techniques](https://scholariq.org/topics/plant-disease-management-techniques/)
- [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.