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

Retrieval of live, user-broadcast video streams is an under-addressed andincreasingly relevant challenge. The on-line nature of the problem requirestemporal evaluation and the unforeseeable scope of potential queries motivatesan approach which can accommodate arbitrary search queries. To account for thebreadth of possible queries, we adopt a no-example approach to query retrieval,which uses a query's semantic relatedness to pre-trained concept classifiers.To adapt to shifting video content, we propose memory pooling and memorywelling methods that favor recent information over long past content. Weidentify two stream retrieval tasks, instantaneous retrieval at any particulartime and continuous retrieval over a prolonged duration, and propose means forevaluating them. Three large scale video datasets are adapted to the challengeof stream retrieval. We report results for our search methods on the new streamretrieval tasks, as well as demonstrate their efficacy in a traditional,non-streaming video task.

Video Stream Retrieval of Unseen Queries using Semantic Memory