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Reverse-SynthID is a research-focused project that analyzes and reverse-engineers Google’s SynthID watermarking system used in AI-generated images. It leverages signal processing and spectralanalysis techniques to identify hidden watermark patterns without access to proprietary encoding methods. The project introduces a multi-resolution “SpectralCodebook” that maps watermark characteristics across different image sizes. Using this approach, it can detect SynthID watermarks with high accuracy and selectively reduce or remove them through frequency-domain manipulation. ...
A Python function library to extract EEG feature from EEG time series in standard Python and numpy data structure. Features include classical spectralanalysis, entropies, fractal dimensions, DFA, inter-channel synchrony and order, etc.