Project-AgML/soybean_weed_uav_brazil

Soybean Weed Uav Brazil

A dataset for image classification of Soybean Weed Uav Brazil. The dataset contains 15,336 images across 4 classes: broadleaf, grass, soil, soybean.
Images per class:

• broadleaf: 1,191
• grass: 3,520
• soil: 3,249
• soybean: 7,376

This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.

Citation

dos Santos Ferreira, Alessandro; Pistori, Hemerson; Matte Freitas, Daniel; Gonçalves da Silva, Gercina (2017), “Data for: Weed Detection in Soybean Crops Using ConvNets”, Mendeley Data, V2, doi: 10.17632/3fmjm7ncc6.2