Infusion Stand Target Detection Image Dataset

The current medical industry faces challenges of low efficiency and high error rates in intelligent recognition and management of infusion stands. Existing manual recognition methods often rely on the experience of medical staff, leading to frequent misdiagnosis and missed diagnoses. To address this issue, this dataset aims to provide high-quality infusion stand image data to support the training of machine learning models, enhancing the accuracy of automatic recognition. Data collection is conducted using professional medical equipment in real hospital environments to ensure the authenticity and effectiveness of the data. In terms of quality control, multiple rounds of annotation and expert review are employed to ensure data consistency and accuracy. The data is stored in JPEG format and organized according to image ID for easy subsequent processing and application.