Categorization of faces using unsupervised feature extraction
Michael Kenyatta Fleming, Garrison W. Cottrell · 1990
The proposal of G. Cottrell et al. (1987) that their image compression network might be used to extract image features for pattern recognition automatically, is tested by training a neural network to compress 64 face images, spanning 11 subjects, and 13 nonface images. Features extracted in this manner (the output of the hidden units) are given as input to a one-layer network trained to distinguish faces from nonfaces and to attach a name and sex to the face images. The network successfully recognizes new images of familiar faces, categorizes novel images as to their `faceness' and, to a great extent, gender, and exhibits continued accuracy over a considerable range of partial or shifted input