{"id":"W2092816422","doi":"10.1109/icce.2011.5722830","title":"A new wavelet-based image watermarking technique","year":2011,"lang":"en","type":"article","venue":"","topic":"Advanced Steganography and Watermarking Techniques","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Northern British Columbia","funders":"","keywords":"Digital watermarking; Watermark; Computer science; Artificial intelligence; Image (mathematics); Wavelet; Computer vision; Gaussian noise; Noise (video); Gaussian; JPEG; Discrete wavelet transform; Wavelet transform","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":[0.0001968491,0.0003298777,0.0003758725,0.0006167258,0.0002400855,0.0004574834,0.0005180279,0.0006881019,0.001644963],"category_scores_gemma":[0.0005292681,0.0001784119,0.000387584,0.0007718832,0.0004991723,0.001485488,0.0005843836,0.0008826295,0.001025662],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001504896,"about_ca_system_score_gemma":0.0002074279,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001234876,"about_ca_topic_score_gemma":0.000207154,"domain_scores_codex":[0.9997503,0.00002054874,0.00001461937,0.00004157535,0.0001528372,0.00002009341],"domain_scores_gemma":[0.9998122,0.00003244509,0.00003978578,0.00005407549,0.00004668227,0.00001478514],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001278698,0.00007963709,0.0002511349,0.0003309685,0.00004807705,0.0003249233,0.00008436602,0.002669688,0.6804626,0.02701538,0.002798863,0.2858065],"study_design_scores_gemma":[0.0001207478,0.0009001754,0.002481672,0.0001450139,0.000229091,0.007684999,0.00008340149,0.1878943,0.6102262,0.01701489,0.1730946,0.0001249186],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03317753,0.004975604,0.9501108,0.0006671431,0.0006673688,0.00009311049,0.0001147403,0.0006820101,0.009511668],"genre_scores_gemma":[0.3312949,0.008903524,0.6296768,0.0006001966,0.0005659453,0.0001204617,0.0002699188,0.0001036666,0.02846465],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001644963,"threshold_uncertainty_score":0.005502999,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02083334618664886,"score_gpt":0.2339062982654929,"score_spread":0.213072952078844,"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."}}