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Few-Shot Training GAN for Face Forgery Classification and Segmentation Based on the Fine-Tune Approa...

Few-Shot Training GAN for Face Forgery Classification and Segmentation Based on the Fine-Tune Approa...

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2791640018

Few-Shot Training GAN for Face Forgery Classification and Segmentation Based on the Fine-Tune Approach

About this item

Full title

Few-Shot Training GAN for Face Forgery Classification and Segmentation Based on the Fine-Tune Approach

Author / Creator

Publisher

Basel: MDPI AG

Journal title

Electronics (Basel), 2023-03, Vol.12 (6), p.1417

Language

English

Formats

Publication information

Publisher

Basel: MDPI AG

More information

Scope and Contents

Contents

There are many techniques for faking videos that can alter the face in a video to look like another person. This type of fake video has caused a number of information security crises. Many deep learning-based detection methods have been developed for these forgery methods. These detection methods require a large amount of training data and thus can...

Alternative Titles

Full title

Few-Shot Training GAN for Face Forgery Classification and Segmentation Based on the Fine-Tune Approach

Authors, Artists and Contributors

Identifiers

Primary Identifiers

Record Identifier

TN_cdi_proquest_journals_2791640018

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2791640018

Other Identifiers

ISSN

2079-9292

E-ISSN

2079-9292

DOI

10.3390/electronics12061417

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