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COLOR REPRESENTATION IN DEEP NEURAL NETWORKS

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Citation Author(s):
Martin Engilberge
Edo Collins, Sabine Süsstrunk
Submitted by:
Martin Engilberge
Last updated:
14 September 2017 - 2:22pm
Document Type:
Poster
Document Year:
2017
Event:
ICIP 2017
Presenters:
Engilberge, Collins
Paper Code:
2886
Categories:
Learning theory and algorithms (MLR-LEAR)
 

Convolutional neural networks are top-performers on image
classification tasks. Understanding how they make use of
color information in images may be useful for various tasks.
In this paper we analyze the representation learned by a popular
CNN to detect and characterize color-related features.
We confirm the existence of some object- and color-specific
units, as well as the effect of layer-depth on color-sensitivity
and class-invariance.

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