Pepper Diseases and Pests Detection

This dataset is a curated collection of images and metadata used for the study titled "A Multi-Modal Framework for Pepper Disease and Pest Detection". The dataset includes high-quality images of pepper plants exhibiting various symptoms of diseases and pest infestations, annotated with relevant metadata for use in machine learning and deep learning applications. It is designed to support researchers and practitioners in developing and evaluating models for accurate disease diagnosis and pest identification in agricultural settings.
This dataset is particularly suited for:

Developing supervised learning models for disease and pest detection.
Training image classification, object detection, and segmentation algorithms.
Evaluating the robustness of algorithms under varying environmental conditions.

Due to confidentiality agreements with agricultural partners, this dataset represents only a subset of the complete data used in the study.
The complete dataset and associated code are available upon request. Please contact the corresponding author for details.
After project completion, the full dataset will be made publicly available on GitHub.

本数据集为一精选图像及元数据集合，旨在支持研究项目《基于多模态框架的辣椒病害与害虫检测》的开展。该数据集包含高质量辣椒植株图像，展示了多种病害及害虫侵害的症状，并附有相关元数据，旨在为机器学习和深度学习应用提供支持。其设计初衷是为研究人员及实践者提供工具，以开发并评估农业环境中病害诊断及害虫识别模型。该数据集尤其适用于以下用途：

* 开发用于病害和害虫检测的监督学习模型。
* 训练图像分类、目标检测及分割算法。
* 评估算法在多变环境条件下的鲁棒性。

鉴于与农业合作伙伴的保密协议，本数据集仅代表研究中所用完整数据的子集。完整数据集及相关代码可在请求后获得，请联系通讯作者获取详细信息。项目完成后，完整数据集将公开发布于GitHub平台。