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 ALADIN (All Layer AdaIN); a novel architecture for searchingimages based on the similarity of their artistic style. Representation learningis critical to visual search, where distance in the learned search embeddingreflects image similarity. Learning an embedding that discriminatesfine-grained variations in style is hard, due to the difficulty of defining andlabelling style. ALADIN takes a weakly supervised approach to learning arepresentation for fine-grained style similarity of digital artworks,leveraging BAM-FG, a novel large-scale dataset of user generated contentgroupings gathered from the web. ALADIN sets a new state of the art accuracyfor style-based visual search over both coarse labelled style data (BAM) andBAM-FG; a new 2.62 million image dataset of 310,000 fine-grained stylegroupings also contributed by this work.

ALADIN: All Layer Adaptive Instance Normalization for Fine-grained Style Similarity