Workflow for Real-Time Sludge Moisture Content Prediction Using Deep Learning. (IMAGE)
Caption
Workflow for Real-Time Sludge Moisture Content Prediction Using Deep Learning. This figure illustrates the workflow for predicting sludge moisture content using deep learning. The process begins with sample preparation (a) and progresses through model construction and comparison (b), identifying the best model (VGG16) (c). Image data is collected from various sludge jet experiments under different pressures and nozzle diameters (d). The optimal model is selected based on jet pressure and diameter correlations (e), followed by accurate moisture content prediction in less than 20 seconds (f).
Credit
Environmental Science and Ecotechnology
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CC BY-NC-ND