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 presents our results and findings on the use of temporal imagesfor deepfake detection. We modelled temporal relations that exist in themovement of 468 facial landmarks across frames of a given video as spatialrelations by constructing an image (referred to as temporal image) using thepixel values at these facial landmarks. CNNs are capable of recognizing spatialrelationships that exist between the pixels of a given image. 10 differentImageNet models were considered for the study.

Deepfake Detection using ImageNet models and Temporal Images of 468 Facial Landmarks