# Automated grapevine flower detection and quantification method based on computer vision and deep learning from on-the-go imaging using a mobile sensing platform under field conditions

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/automated-grapevine-flower-detection-and-quantification-method-based-on-computer/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Fernando Palacios,Gloria Bueno,Jesús Salido,María P. Diago,Inés Hernández,Javier Tardáguila |
| Citations | 82 |
| DOI | 10.1016/j.compag.2020.105796 |
| Fields | Agricultural and Biological Sciences,Environmental Science |
| Open Access | false |
| OA Status | closed |
| OpenAlex ID | https://openalex.org/W3088481470 |
| Type | article |
| Year | 2020 |

## Paper authors

- [Inés Hernández](https://scholariq.org/researchers/ines-hernandez/)

## Paper journal

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

## Paper primary topic

- [Horticultural and Viticultural Research](https://scholariq.org/topics/horticultural-and-viticultural-research/)

## Paper topics

- [Horticultural and Viticultural Research](https://scholariq.org/topics/horticultural-and-viticultural-research/)
- [Smart Agriculture and AI](https://scholariq.org/topics/smart-agriculture-and-ai/)
- [Remote Sensing in Agriculture](https://scholariq.org/topics/remote-sensing-in-agriculture/)

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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.