A system may include at least one processor configured to: obtain a trained neural network (NN); obtain or calculate at least one average feature information associated with the trained NN, each of the at least one average feature information including a given average feature information summarizing in-class statistics that each layer of the trained NN uses for a given class; receive an incoming observation influencing a given layer; calculate a corresponding feature information of the incoming observation, the corresponding feature information summarizing statistics of the incoming observation for the given layer; classify the incoming observation as being in the given class; calculate a distance score associated with a distance between the corresponding feature information of the incoming observation and the given average feature information; determine the incoming observation is an out-of-distribution (OOD) sample; and output an alert indicating the incoming observation is OOD and/or discard the incoming observation's classification.