  One of the salient features of human perception is its invariance under
dilatation in addition to the Euclidean group, but its non-invariance under
special conformal transformation. We investigate a holographic approach to the
information processing in image discrimination with this feature. We claim that
a strongly coupled analogue of the statistical model proposed by Bialek and Zee
can be holographically realized in scale invariant but non-conformal Euclidean
geometries. We identify the Bayesian probability distribution of our
generalized Bialek-Zee model with the GKPW partition function of the dual
gravitational system. We provide a concrete example of the geometric
configuration based on a vector condensation model coupled with the Euclidean
Einstein-Hilbert action. From the proposed geometry, we study sample
correlation functions to compute the Bayesian probability distribution.
