Comparison of Mean Absolute Error (MAE) in Millimeters as a Function of Kernel Size. - Liu Liu (512237) (2025)
Fig 8 presents the mean absolute error (MAE) in millimeters as a function of kernel size (in pixels) for two model configurations. The red line, marked with circles, corresponds to the ‘Full Model’, while the blue line, marked with ‘X’ symbols, represents the ‘Reduced Depth’ version. The graph tracks the performance of both models across kernel sizes ranging from 100 to 300 pixels. The Full Model generally maintains a lower MAE, suggesting higher accuracy than the Reduced Depth model. Both models show a decrease in MAE as the kernel size increases up to approximately 200 pixels. After this point, the Reduced Depth model’s MAE increases significantly, while the Full Model’s performance stabilizes before slightly increasing again.