/Weed-Detection-in-Soybean-Crops

Weed Detection in Soybean Crops Numpy Implementation

Primary LanguageJupyter Notebook

Weed-Detection-in-Soybean-Crops Numpy Implementation

Weed Detection in Soybean Crops

Context

From the set of images captured by the UAV, all those with occurrence of weeds were selected resulting a total of 400 images. Through the Pynovisão software, using the SLIC algorithm, these images were segmented and the segments annotated manually with their respective class. These segments were used in the construction of the image dataset.

Content

This image dataset has 15336 segments, being 3249 of soil, 7376 of soybean, 3520 grass and 1191 of broadleaf weeds.

Acknowledgements

This dataset was created by Alessandro dos Santos Ferreira, Hemerson Pistori, Daniel Matte Freitas and Gercina Gonçalves da Silva. It is distributed under the CC BY NC 3.0 license.

DOI: 10.17632/3fmjm7ncc6.2

Original URL: https://data.mendeley.com/datasets/3fmjm7ncc6/2