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Using Bilevel Feature Extractors to Reduce Dimensionality in Images

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2 Author(s)
Joliveau, M. ; Univ. de Montreal, Montréal, QC, Canada ; Gendreau, M.

A bilevel procedure for dimensionality reduction makes it possible to discover the underlying global geometry of a complex natural observations dataset-such as human handwriting or faces under different viewing positions-with higher precision than existing methods.

Published in:

Computing in Science & Engineering  (Volume:14 ,  Issue: 3 )