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 Tools annual

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 Tools monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

There exists a problem that it is difficult to identify the authenticity of offline signatures. Firstly, a segmentation model is established based on the theory of fuzzy sets to extract signatures completely. Secondly, statistical shape model (SSM) and variance distance discretization of intraclass signatures are introduced for stability analysis and quantification. Finally, multilayer classifiers are constructed to realize signature authentication. The algorithm has low false detection rate and short authentication time.

Offline Signature Authentication Algorithm Based on the Fuzzy Set