MSRD-CNN: Multi-Scale Residual Deep CNN for General-Purpose Image Manipulation Detection
The authenticity of digital images is a major concern in multimedia forensics due to the availability of advanced photo editing tools/devices. In the literature, several image forensic methods are available to detect specific image processing or editing operations. However, it remains a challenging...
Saved in:
Main Authors: | Kapil Rana, Gurinder Singh, Puneet Goyal |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2022-01-01
|
Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/9758710/ |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Residual Life Prediction of SA-CNN-BILSTM Aero-Engine Based on a Multichannel Hybrid Network
by: Yonghao He, et al.
Published: (2025-01-01) -
Remaining Useful Life Prediction of Rolling Bearings Based on CBAM-CNN-LSTM
by: Bo Sun, et al.
Published: (2025-01-01) -
Enhancing plant disease detection through deep learning: a Depthwise CNN with squeeze and excitation integration and residual skip connections
by: Asadulla Y. Ashurov, et al.
Published: (2025-01-01) -
A generative adversarial network with multiscale and attention mechanisms for underwater image enhancement
by: Liquan Zhao, et al.
Published: (2025-01-01) -
RBMDC-Net: Effective Jaw Cyst Segmentation Network Using Residual Bottleneck and Multiscale Dilated Convolution
by: Huixia Zheng, et al.
Published: (2025-01-01)