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

With the growing computer vision applications, lots of videos are transmittedfor content analysis, the way to allocate resources can affect the performanceof video content analysis. For this purpose, the traditional resourceallocation schemes for video transmission in vehicular networks, such asqualityof-service (QoS) based or quality-of-experience (QoE) based schemes, areno longer optimal anymore. In this paper, we propose an efficient contentdriven resource allocation scheme for vehicles equipped with cameras underbandwidth constraints in order to improve the video content analysisperformance. The proposed resource allocation scheme is based on maximizing thequality-of-content (QoC), which is related to the content analysis performance.A QoC based assessment model is first proposed. Then, the resource allocationproblem is converted to a solvable convex optimization problem. Finally,simulation results show the better performance of our proposed scheme than theexisting schemes like QoE based schemes.

A Content Driven Resource Allocation Scheme for Video Transmission in Vehicular Networks