English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Tools annual

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

Selfridge, along with Sutherland and Marr provided some of the earliestproposals for how to program computers to recognize shapes. Their emphasis onfiltering for contour features, especially the orientation of boundarysegments, was reinforced by the Nobel Prize winning work of Hubel & Wiesel whodiscovered that neurons in primary visual cortex selectively respond as afunction of contour orientation. Countless investigators and theorists havecontinued to build on this approach. These models are often described asneuromorphic, which implies that the computational methods are based onbiologically plausible principles. Recent work from the present lab haschallenged the emphasis on orientation selectivity and the use of neuralnetwork principles. The goal of the present report is not to relitigate thoseissues, but to provide an alternative concept for encoding of shape informationthat may be useful to neuromorphic modelers.

Scan transcription of two-dimensional shapes as an alternative neuromorphic concept