An intelligent camera surveillance system is supposed to autonomously detect stray pieces of luggage or other suspicious objects at a railway station. To do this, it has to know what suitcases and bags look like. To achieve this, humans have to feed the system with training data - in this case with as many images as possible of different pieces of luggage.
A form of machine learning called reinforcement learning works in a completely different way. "Data input from humans is not necessary here," says computer science professor Carlo D’Eramo. ...
