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

This paper introduces the first dataset of satellite images labeled withforage quality by on-the-ground experts and provides proof of concept forapplying computer vision methods to index-based drought insurance. We alsopresent the results of a collaborative benchmark tool used to crowdsource anaccurate machine learning model on the dataset. Our methods significantlyoutperform the existing technology for an insurance program in Northern Kenya,suggesting that a computer vision-based approach could substantially benefitpastoralists, whose exposure to droughts is severe and worsening with climatechange.

Satellite-based Prediction of Forage Conditions for Livestock in Northern Kenya