FIGURE 2.

A schematic overview of the FFN and CNN architectures used in this study. (a) FFN architecture; DL#1 (8 units) and DL#2 (4 units) are both dense layers. (b) CNN architecture; CL #1 represents a convolutional layer (8 filters), FL represents a Flatten layer, and DL represents a dense layer (4 units). In (b), the dotted lines illustrate how each part of the input is processed by different filters in the convolutional layers, visually representing the learning process and the interaction of various filters with different regions of the input data.