Using Machine Learning in a Complex Environment

The deep learning methods came after, came when we were thinking about the postla ground surface displacement ithing. And actually, because we had this problem in the isarinteprogramo data, it's not straightforward to distinguish between the noisy part and the useful part. So what we did is that we tried to explore the deplored incapability to have a straightforward method of classification to distinguish tesumen that is effected by fist plat deformation and the zone that it is only the atmospheric noise dide.