Work

A UAV image dataset for object detection with annotations generated using LabelImg and Roboflow

Year: 2026

Type: data-paper

Abstract: The dataset consists of drone images of cotton fields which were created to aid precision agriculture and machine learning-based weed detection research. The main goal is to enable the creation of object detection models for crop-weed differentiation while providing a standard for model evaluation. The dataset release serves two purposes: it supports the advancement of automated agricultural monitoring and sustainable farming practices, and it adds to the expanding research on AI solutions for agricultural productivity and environmental management.

Source: Data in Brief

DOI: 10.1016/j.dib.2026.112483

Authors: Anindita Das, Vinitha Hannah Subburaj, Yong Yang, Craig W. Bednarz

Institution: West Texas A&M University

Language: English

Topic: Smart Agriculture and AI

Subfield: Plant Science

Field: Agricultural and Biological Sciences

Domain: Life Sciences

SDG: Zero hunger

Open Access status: gold

Estimated APC paid: $1,220