Multi-Scenario Remote Sensing Image Forgery Detection Based on Transformer and Model Fusion
Recently, remote sensing image forgery detection has received widespread attention. To improve the detection accuracy, we build a novel scheme based on Transformer and model fusion. Specifically, we model this task as a binary classification task that focuses on global information. First, we explore...
Saved in:
| Main Authors: | Jinmiao Zhao, Zelin Shi, Chuang Yu, Yunpeng Liu |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2024-11-01
|
| Series: | Remote Sensing |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2072-4292/16/22/4311 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
DFST-UNet: Dual-Domain Fusion Swin Transformer U-Net for Image Forgery Localization
by: Jianhua Yang, et al.
Published: (2025-05-01) -
solving the problematic of the application of the legal provions to the material element of the crime of forgery of public or official documents in accordance with Law 24-02 relating to the fight against forgery and the use of forgery
by: Ahmed Hemmi
Published: (2025-06-01) -
Forgery of Icons
by: Julia Spies
Published: (2009-04-01) -
Copy-Move Forgery Verification in Images Using Local Feature Extractors and Optimized Classifiers
by: S. B. G. Tilak Babu, et al.
Published: (2023-09-01) -
MFFNet: a wavelet transform-based multimodal frequency fusion network for remote sensing semantic segmentation
by: Chao Li, et al.
Published: (2025-12-01)