I used a convolutional neural net for face recognition on a hobby project, but I kept getting issues where the probability of matching a face was high so long as a face was actually in the image. Unfortunately, this didnt work well with a sliding window algo because Id get a bunch of windows with a high probability of a face with the only difference being a slight shift in increment / size. Would it be better to just use a multi layer perceptron? Also, does anyone else find it amusing when their face recognition systems identify things like toes or gates with high confidence? I end up spending some time zooming in to make sure it's not one of those hidden faces in random images