Image Dataset of Water Samples with Suspended Solids under Stroboscopic Light for Deep Learning Classification

This dataset contains labeled images of water samples with varying concentrations of total suspended solids (TSS), acquired under controlled experimental conditions using a stroboscopic white light illumination system. Water samples were prepared using distilled water and controlled concentrations of suspended solids ranging from 40 to 6000 mg/L, allowing classification into four water quality levels: good, acceptable, contaminated, and strongly contaminated. Images were captured under controlled acquisition conditions to evaluate the influence of illumination variability on the performance of deep learning models for water quality classification. The dataset supports research in computer vision and machine learning, particularly in evaluating the robustness of convolutional neural networks under different lighting conditions.