Infusion Stand Model and Material Classification Image Dataset

In the medical industry, infusion stands are important equipment. With medical technology advancements, various models and materials of infusion stands have appeared on the market. However, there is still a lack of systematic classification data for different models and materials, posing challenges for medical institutions in equipment management and selection. Current solutions often rely on manual annotation or experiential judgment, resulting in inconsistency and inefficiency in labeling. This dataset aims to provide a comprehensive infusion stand classification image dataset to solve the problem of data scarcity in equipment management and enable intelligent management and decision support. The dataset is collected using high-resolution cameras in hospital environments, covering various models and materials, ensuring data diversity and representativeness. To ensure data quality, a dual annotation and expert review method is used for quality control to ensure labeling consistency and accuracy. All data is stored in JPG format and organized by category for ease of subsequent analysis and application.