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- W4378651398 abstract "Deep learning has achieved tremendous success in low-level computer vision tasks such as image processing tasks. To protect the intellectual property (IP) of such valuable image processing networks, the model vendor can sell the service in the manner of the application program interface (API). However, even if the attacker can only query the API, he is still able to conduct model extraction attacks, which can steal the functionality of the target networks. In this chapter, we propose a new model watermarking framework for image processing networks. Under the framework, two strategies are further developed, namely, the model-agnostic strategy and the model-specific strategy. The proposed watermarking method performs well in terms of fidelity, capacity, and robustness." @default.
- W4378651398 created "2023-05-30" @default.
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- W4378651398 date "2022-11-28" @default.
- W4378651398 modified "2023-09-26" @default.
- W4378651398 title "Protecting Image Processing Networks via Model Watermarking" @default.
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- W4378651398 doi "https://doi.org/10.1007/978-981-19-7554-7_6" @default.
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