农业大数据学报2025，Vol.7Issue(3)：371-378,8.DOI:10.19788/j.issn.2096-6369.100060
基于人工标注与对比生成模型的玉米叶病图文多模态数据集
Image-Text Multi-Modal Dataset of Corn Leaf Diseases based on Manual Annotation and Contrast Generation Model
摘要
Abstract
Accurately identifying corn leaf diseases is an important part of intelligent agricultural management.The existing maize disease data sets have problems such as uneven quality,fuzzy label categories,and lack of multimodal data,especially the scarcity of disease description data in the Chinese context.This data set integrates the image data of corn disease from open source platforms such as AI Challenger,PlantVillage and OpenDataLab,and complements the high-definition disease images collected in the field.A Chinese multimodal data set containing 1653 images is constructed.Each image has its corresponding diagnostic text description,covering key information such as disease type,disease characteristics and severity.At the same time,the cn-clip and CPT2 Chinese large model are combined to achieve image description generation,which provides a method for automatic annotation.This data set can provide high-quality data support for the development of an intelligent diagnosis model of corn disease,the generation of Chinese image description and the construction of an agricultural multimodal knowledge map.关键词
玉米/叶部病害/多模态数据集/图像描述/自动标注Key words
corn/leaf diseases/multimodal data set/image description/automatic annotation引用本文复制引用
王彦芳,鲜国建,赵瑞雪..基于人工标注与对比生成模型的玉米叶病图文多模态数据集[J].农业大数据学报,2025,7(3):371-378,8.基金项目
新一代人工智能国家科技重大专项(2021ZD0113705). （2021ZD0113705）
