Sleep Monitoring Device Target Detection Image Dataset

In the current medical industry, the use of sleep monitoring devices is becoming increasingly common. However, due to the lack of high-quality image datasets, the accuracy and robustness of machine learning models are insufficient. Existing solutions mainly rely on small-scale datasets, which results in poor performance of models in practical applications. Therefore, this dataset aims to provide a rich image dataset for sleep monitoring devices to solve the data scarcity problem in target detection and classification tasks. Data collection is performed using high-resolution cameras in real sleep monitoring environments to ensure the authenticity and diversity of the images. Quality control measures include multiple rounds of annotation and expert review to ensure each image is rigorously validated. Data is stored in JPG format and organized in a certain directory structure to facilitate subsequent model training and evaluation.