English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

The study of the visual system of the brain has attracted the attention andinterest of many neuro-scientists, that derived computational models of sometypes of neuron that compose it. These findings inspired researchers in imageprocessing and computer vision to deploy such models to solve problems ofvisual data processing. In this paper, we review approaches for imageprocessing and computer vision, the design of which is based onneuro-scientific findings about the functions of some neurons in the visualcortex. Furthermore, we analyze the connection between the hierarchicalorganization of the visual system of the brain and the structure ofConvolutional Networks (ConvNets). We pay particular attention to themechanisms of inhibition of the responses of some neurons, which provide thevisual system with improved stability to changing input stimuli, and discusstheir implementation in image processing operators and in ConvNets.

Brain-inspired algorithms for processing of visual data