  Recently DCNN (Deep Convolutional Neural Network) has been advocated as a
general and promising modelling approach for neural object representation in
primate inferotemporal cortex. In this work, we show that some inherent
non-uniqueness problem exists in the DCNN-based modelling of image object
representations. This non-uniqueness phenomenon reveals to some extent the
theoretical limitation of this general modelling approach, and invites due
attention to be taken in practice.
