2024
DOI: 10.3390/app14114882
|View full text |Cite
|
Sign up to set email alerts
|

An Audio Copy-Move Forgery Localization Model by CNN-Based Spectral Analysis

Wei Zhao,
Yujin Zhang,
Yongqi Wang
et al.

Abstract: In audio copy-move forgery forensics, existing traditional methods typically first segment audio into voiced and silent segments, then compute the similarity between voiced segments to detect and locate forged segments. However, audio collected in noisy environments is difficult to segment and manually set, and heuristic similarity thresholds lack robustness. Existing deep learning methods extract features from audio and then use neural networks for binary classification, lacking the ability to locate forged s… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

0
0
0

Publication Types

Select...

Relationship

0
0

Authors

Journals

citations
Cited by 0 publications
references
References 23 publications
0
0
0
Order By: Relevance

No citations

Set email alert for when this publication receives citations?