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

There is a growing privacy concern due to the popularity of social media andsurveillance systems, along with advances in face recognition software.However, established image obfuscation techniques are either vulnerable tore-identification attacks by human or deep learning models, insufficient inpreserving image fidelity, or too computationally intensive to be practical. Totackle these issues, we present DeepBlur, a simple yet effective method forimage obfuscation by blurring in the latent space of an unconditionallypre-trained generative model that is able to synthesize photo-realistic facialimages. We compare it with existing methods by efficiency and image quality,and evaluate against both state-of-the-art deep learning models and industrialproducts (e.g., Face++, Microsoft face service). Experiments show that ourmethod produces high quality outputs and is the strongest defense for most testcases.

DeepBlur: A Simple and Effective Method for Natural Image Obfuscation