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K. Gegenfurtner

4 papers here

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • last author4

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CV4

identity via Semantic Scholar / OpenAlex

activity
20182020
most citedParadox in Deep Neural Networks: Similar yet Different while Different yet Similar

3 citations · 7 across the 3 of their papers we have counts for

collaborators

4 papers

cs.CV2020★ 3 cited

Deep Neural Models for color discrimination and color constancy

Alban Flachot, Arash Akbarinia, Heiko H. Schütt +3

Color constancy is our ability to perceive constant colors across varying illuminations. Here, we trained deep neural networks to be color constant and evaluated their performance…

cs.CV2019★ 3 cited

Paradox in Deep Neural Networks: Similar yet Different while Different yet Similar

Arash Akbarinia, Karl R. Gegenfurtner

Machine learning is advancing towards a data-science approach, implying a necessity to a line of investigation to divulge the knowledge learnt by deep neuronal networks. Limiting t…

cs.CV2019★ 1 cited

Manifestation of Image Contrast in Deep Networks

Arash Akbarinia, Karl R. Gegenfurtner

Contrast is subject to dramatic changes across the visual field, depending on the source of light and scene configurations. Hence, the human visual system has evolved to be more se…

cs.CV2018

How is Contrast Encoded in Deep Neural Networks?

Arash Akbarinia, Karl R. Gegenfurtner

Contrast is a crucial factor in visual information processing. It is desired for a visual system - irrespective of being biological or artificial - to "perceive" the world robustly…

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