Estimating particle size in silty lake sediments using a fine-tuned deep learning model on hyperspectral imagery

• Hyperspectral imaging effectively captured grain-size variations in the silt range. • Model performance remained significant using only 24% of original training data. • Performance did not substantially improved by including more than 48% of training data. • Lithofacies properties showed no apparent relationship with model performance.