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Reinforced Multi-Teacher Knowledge Distillation For Efficient General Image Forgery Detection and Localization by Amir Shahzad is a document available to read on EtoBox.
What is Reinforced Multi-Teacher Knowledge Distillation For Efficient General Image Forgery Detection and Localization about?
The document presents a novel Reinforced Multi-teacher Knowledge Distillation (Re-MTKD) framework for efficient image forgery detection and localization (IFDL), addressing the limitations of previous methods in handling diverse forgery types. The framework utilizes multiple Cue-Net models trained on specific forgery types and incorporates a Reinforced Dynamic Teacher Selection strategy to enhance knowledge transfer to a student model. Experimental results demonstrate that the proposed method outperforms sta
- Author
- Amir Shahzad
- Language
- EN