LDD: A Dataset for Grape Diseases Object Detection and Instance Segmentation

LDD数据集由意大利帕尔马大学的IMP实验室创建，专注于葡萄疾病的对象检测和实例分割。该数据集包含1,092张图像，涵盖了10种对象类型，包括带有8种常见葡萄疾病症状的叶子和葡萄。数据集的创建旨在通过实例分割技术，提高葡萄疾病早期检测的准确性和效率。创建过程中，图像收集自Horta的内部数据库和网络，所有分割均由作者手动完成。LDD数据集的应用领域主要集中在精准农业，特别是葡萄园的疾病管理和控制，以支持可持续农业实践和提高食品安全。

The LDD dataset was developed by the IMP Laboratory at the University of Parma, Italy, and focuses on object detection and instance segmentation for grape diseases. It contains 1,092 images covering 10 object categories, including leaves and grape clusters showing symptoms of 8 common grape diseases. This dataset was created to improve the accuracy and efficiency of early grape disease detection through instance segmentation techniques. During its development, images were collected from Horta's internal database and the web, and all segmentations were manually performed by the authors. The main application areas of the LDD dataset are centered on precision agriculture, particularly disease management and control in vineyards, to support sustainable agricultural practices and enhance food safety.

搜集汇总

背景与挑战

背景概述

LDD数据集由意大利帕尔马大学IMP实验室创建，包含1,092张图像，涵盖10种对象类型，专注于葡萄疾病的对象检测和实例分割。该数据集旨在通过手动完成的实例分割技术，提高葡萄疾病早期检测的准确性和效率，主要应用于精准农业中的葡萄园疾病管理和控制，以支持可持续农业实践和食品安全。