Lincolnbeet

Lincolnbeet 数据集是一个对象检测数据集，旨在鼓励研究在高遮挡环境中识别项目，并开发更好的方法来评估实际场景中的对象检测模型。该数据集在论文中介绍：“精准农业中杂草喷洒的实用对象检测”。
该数据集包含 4402 张图像，其中包含杂草植物和甜菜，这些图像带有对象检测标签。图像大小为 1920 x 1080 像素，数据集中包含的标签为 COCOjson、XML 和 darknets 格式。

The Lincolnbeet dataset is an object detection dataset intended to promote research on object recognition in highly occluded environments and the development of improved approaches for evaluating object detection models in real-world scenarios. This dataset was introduced in the paper titled "Practical Object Detection for Weed Spraying in Precision Agriculture".

This dataset contains 4402 images depicting weed plants and sugar beets, all annotated with object detection labels. The images have a resolution of 1920 x 1080 pixels, and the annotations in this dataset are available in COCO JSON, XML, and Darknet formats.

搜集汇总

背景与挑战

背景概述

Lincolnbeet是一个对象检测数据集，包含4402张高分辨率图像，用于研究高遮挡环境下的杂草和甜菜识别，支持多种标签格式，适用于精准农业研究。