A curriculum-based loss scheduler for steganography trains first on embedding quality, then decoding, then steganalysis resistance, but its security gains are inconsistent across datasets.
An improved steganography without embedding based on attention gan
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TSCL:Multi-party loss Balancing scheme for deep learning Image steganography based on Curriculum learning
A curriculum-based loss scheduler for steganography trains first on embedding quality, then decoding, then steganalysis resistance, but its security gains are inconsistent across datasets.