<ul><li>Fruit drying is an important process in food manufacturing for reducing moisture content, ensuring product safety, and extending shelf life.</li><li>A new multi-modal data fusion framework has been proposed to improve the accuracy of moisture content prediction in apple drying.</li><li>The framework effectively combines tabular data (process parameters) and high-dimensional image data (images of dried apple slices).</li><li>Experimental validation demonstrated significant improvement in predictive accuracy compared to existing methods.</li></ul>

Multi-Modal Data Fusion for Moisture Content Prediction in Apple Drying

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