A Space-Variant Visual Pathway Model for Data Efficient Deep Learning
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Updated: Jan 26, 2026

A Virtual Machine Platform for Non-Computer Professionals for Using Deep Learning to Classify Biological Sequences of Metagenomic Data
Published on: September 25, 2021
Piotr Ozimek1, Nina Hristozova1, Lorinc Balog1
1Computer Vision for Autonomous Systems Group, School of Computing Science, University of Glasgow, Glasgow, United Kingdom.
Abstract:
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 one million pixels in size, in real time, using only consumer grade graphics processor (GPU) hardware in a single pass of the DCNN.
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