TOM2024

The TOM2024 dataset is a valuable resource for agricultural research, comprising 25,844 raw images and 12,227 labeled images of tomato, onion, and maize crops. These images are categorized into 30 classes, facilitating precise identification of pests and diseases, which is crucial for improving crop management and food security. The dataset supports sustainable agriculture by promoting early and accurate pest and disease detection, reducing reliance on pesticides. Its accessibility allows researchers and institutions to develop advanced digital solutions, enhancing the effectiveness of pest and disease management. Additionally, the dataset's versatility—searchable by region, crop type, and other criteria—makes it suitable for model development, education, and agricultural extension services. With high-resolution images captured under diverse environmental conditions, TOM2024 offers a robust foundation for training AI models, ultimately contributing to the advancement of precision agriculture.

TOM2024数据集是农业研究领域的宝贵资源，包含25844张原始图像与12227张标注图像，涵盖番茄、洋葱及玉米三类作物。该数据集被划分为30个类别，可实现病虫害的精准识别，这对于优化作物管理、保障粮食安全具有关键意义。
本数据集通过推动早期精准的病虫害检测、降低农药依赖，为可持续农业发展提供支撑。其开放的可访问性可助力研究人员与科研机构开发先进的数字化解决方案，提升病虫害治理的有效性。
此外，该数据集具备多维度适用性——支持按区域、作物类型及其他标准进行检索，可广泛应用于模型开发、教育教学与农业推广服务。
凭借在多样化环境条件下采集的高分辨率图像，TOM2024为人工智能（AI）模型训练提供了稳固的基础，最终将推动精准农业的发展进步。

搜集汇总

背景与挑战

背景概述

TOM2024是一个农业研究数据集，包含25,844张原始图像和12,227张标记图像，涵盖番茄、洋葱和玉米作物的30个类别，用于害虫和疾病识别。数据集支持可持续农业和AI模型训练，具有高分辨率图像和多样环境条件。