I have recently confronted with a (at least for me) new kind of ML problem, where the output of the model should be a vector/matrix (depending on the interpretation, but there is no difference actually), not a scalar as usual. This is totally unknown for me. What kind of approach should one apply here? Are the "usual" (scalar-based) models applicable on this problem?
(Just for the sake of completeness, the problem is an image segmentation task where the model should decide first: if there a given pattern on the picture?, second: if so, where is it? - In latter case, it should define the borders of the subset pixels).