A Space-Variant Visual Pathway Model for Data Efficient Deep Learning

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 D...

Descripción completa

Detalles Bibliográficos
Autores principales: Ozimek, Piotr, Hristozova, Nina, Balog, Lorinc, Siebert, Jan Paul
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2019
Materias:
Neuroscience
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6444208/
https://www.ncbi.nlm.nih.gov/pubmed/30971891
http://dx.doi.org/10.3389/fncel.2019.00036
Descripción
Sumario: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.

Ejemplares similares