A Space-Variant Visual Pathway Model for Data Efficient Deep Learning.
Ontology highlight
ABSTRACT:
SUBMITTER: Ozimek P
PROVIDER: S-EPMC6444208 | biostudies-literature | 2019
REPOSITORIES: biostudies-literature
Publications
A Space-Variant Visual Pathway Model for Data Efficient Deep Learning.
Ozimek Piotr P Hristozova Nina N Balog Lorinc L Siebert Jan Paul JP
Frontiers in cellular neuroscience 20190326
We present an investigation into adopting a model of the retino-cortical mapping, found in biological visual systems, to improve the efficiency of image analysis using Deep Convolutional Neural Nets (DCNNs) in the context of robot vision and egocentric perception systems. This work has now enabled DCNNs to process input images approaching <i>one million pixels</i> in size, <i>in real time</i>, using only consumer grade graphics processor (GPU) hardware <i>in a single pass of the DCNN</i>. ...[more]
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