I do have about 700 matrices (200*200 pixels) and I would like to cluster them into 5-10 groups.
I wanted to try the k-medoids method for this but am not sure how to implement it. According to what I found out I would have to convert the 200*200 matrix into a 40000 element vector and then use that as input to the clustering. However I am not very convinced about the ability of this algorithm to handle such high dimensional data.
I read about convolutional neural networks and it seemed more suitable. However I would like to know if there is maybe a simpler algorithm that could do the job instead.