Fig. 1.

The difference between the traditional autoencoder network (top) and our proposed MAMA Net (bottom) and its main components. Both are trained on normal items as the gray line and tested on new normal cases as the blue line and anomaly as the red line. In the training phase, the memory module is updated with prototypical normal items as plus sign. And in the testing process, the memory module is fixed and both normal cases and anomaly are addressed via hamming distance.