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

We present a novel bi-modal system based on deep networks to address theproblem of learning associations and simple meanings of objects depicted in"authored" images, such as fine art paintings and drawings. Our overall systemprocesses both the images and associated texts in order to learn associationsbetween images of individual objects, their identities and the abstractmeanings they signify. Unlike past deep nets that describe depicted objects andinfer predicates, our system identifies meaning-bearing objects ("signifiers")and their associations ("signifieds") as well as basic overall meanings fortarget artworks. Our system had precision of 48% and recall of 78% with an F1metric of 0.6 on a curated set of Dutch vanitas paintings, a genre celebratedfor its concentration on conveying a meaning of great import at the time oftheir execution. We developed and tested our system on fine art paintings butour general methods can be applied to other authored images.

Extracting associations and meanings of objects depicted in artworks through bi-modal deep networks