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 Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

The availability of sensor-rich smart wearables and tiny, yet capable,unmanned vehicles such as nano quadcopters, opens up opportunities for a novelclass of highly interactive, attention-shared human--machine teams. Reliable,lightweight, yet passive exchange of intent, data and inferences within suchhuman--machine teams make them suitable for scenarios such as search-and-rescuewith significantly improved performance in terms of speed, accuracy andsemantic awareness. In this paper, we articulate a vision for such human--droneteams and key technical capabilities such teams must encompass. We presentTagTeam, an early prototype of such a team and share promising demonstration ofa key capability (i.e., motion awareness).

TagTeam: Towards Wearable-Assisted, Implicit Guidance for Human--Drone Teams