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Population codes for orientation estimation

Authors: Niklas Lüdtke; Richard C. Wilson 0001; Edwin R. Hancock;

Population codes for orientation estimation

Abstract

Population coding has become an essential paradigm in cognitive neuroscience over the past decade and is increasingly studied within the neural network community. We investigate the use of population vector decoding for local edge orientation estimation from a discrete set of Gabor filters. Vectorial combination of the broadly tuned filter outputs yields a resultant population vector, which gives a precise and robust estimate of the local contour orientation. We present results on the accuracy and robustness of orientation measurement.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
3
Average
Average
Average
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