{"id":"W2141641536","doi":"10.1109/ccece.2004.1345085","title":"A rectification method for RST invariant digital image watermarking","year":2004,"lang":"en","type":"article","venue":"","topic":"Advanced Steganography and Watermarking Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Digital watermarking; Scaling; Rectification; Robustness (evolution); Invariant (physics); Artificial intelligence; Image translation; Computer science; Translation (biology); Computer vision; Rotation (mathematics); Image rectification; Algorithm; Phase correlation; Watermark; Transformation (genetics); Image (mathematics); Mathematics; Geometry; Mathematical analysis; Physics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003527929,0.0005558053,0.0004980991,0.001006931,0.0003501951,0.0004538283,0.0005779293,0.0007516319,0.003746632],"category_scores_gemma":[0.000883857,0.0002743482,0.0005069876,0.0005854107,0.0004830677,0.0009422475,0.000362527,0.000772316,0.001868451],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002883806,"about_ca_system_score_gemma":0.0003049399,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000537781,"about_ca_topic_score_gemma":0.0005399509,"domain_scores_codex":[0.9996583,0.00004057887,0.00001960265,0.00007086853,0.000189988,0.00002075121],"domain_scores_gemma":[0.999666,0.00008501799,0.00004822989,0.00008092206,0.0001079727,0.00001181325],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001577195,0.00004217138,0.0002924983,0.0002132191,0.00003124636,0.00020178,0.0001079932,0.008426739,0.2766531,0.01239138,0.002808933,0.6986732],"study_design_scores_gemma":[0.0001329551,0.0006325765,0.002535033,0.00006370324,0.0001048438,0.00417281,0.00007969963,0.4137868,0.4788654,0.007519651,0.09190051,0.0002060233],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.008542004,0.0007372552,0.9874227,0.0001280447,0.0001395379,0.00005756526,0.00003182164,0.0009834478,0.001957644],"genre_scores_gemma":[0.1229264,0.001346115,0.8648434,0.00009504171,0.0002506053,0.0001098463,0.0001889225,0.0001491172,0.01009066],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003746632,"threshold_uncertainty_score":0.01253372,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01771867608288665,"score_gpt":0.2840292068626761,"score_spread":0.2663105307797894,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}