CAMU-Net: Copy-move forgery detection utilizing coordinate attention and multi-scale feature fusion-based up-sampling

Computer Science

• Feature Fusion 100%
• Copy-Move Forgery Detection 100%
• Copy Move Forgery 100%
• Baseline Method 50%
• Global Feature 50%
• Attention (Machine Learning) 50%
• Traditional Method 50%
• Forgery Detection 50%
• Feature Information 50%
• Obtain Evidence 50%
• Detection Method 50%
• Resource Allocation 50%
• Feature Extraction 50%
• Feature Map 50%
• Deep Learning Method 50%