Figure 3. Uniform Manifold Approximation and Projection (UMAP) of Feature Maps of Images.

A UMAP was created using the average pooling layer in the model trained on images from both North America and Nepal. Each feature map was reduced to 2 (unitless) dimensions and labeled based on stage and the dataset of origin. The clustering of labeled images demonstrates that the model learned not only the image features associated with the presence of stage, but also with the dataset of origin.