{"id":"W24206823","doi":"10.1016/j.nut.2013.07.021","title":"Image Ownership Verification via Private Pattern and Watermarking Wavelet Filters","year":2003,"lang":"en","type":"article","venue":"Digital Image Computing: Techniques and Applications","topic":"Advanced Steganography and Watermarking Techniques","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Dairy Farmers of Canada; Danone","keywords":"Watermark; Wavelet; Digital watermarking; Robustness (evolution); Computer science; Computer vision; Artificial intelligence; Invisibility; Wavelet transform; Key (lock); Image (mathematics); Pattern recognition (psychology); Computer security","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003140117,0.0001708596,0.0002333053,0.0003004699,0.0001174705,0.000381693,0.0002258197,0.0005226456,0.002394733],"category_scores_gemma":[0.002900065,0.0001312947,0.0001524129,0.0002581216,0.0002810723,0.001147853,0.0003279899,0.0002863158,0.0003986542],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001166485,"about_ca_system_score_gemma":0.0001783621,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003178832,"about_ca_topic_score_gemma":0.0004315093,"domain_scores_codex":[0.9997621,0.00004790674,0.00001323282,0.0000495454,0.00008944014,0.00003781836],"domain_scores_gemma":[0.9991416,0.0003555112,0.0001859719,0.000169404,0.0001163693,0.00003124992],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.003872652,0.0003799775,0.009141142,0.0001394742,0.00006985514,0.0004140972,0.0001501739,0.007038272,0.2892829,0.006149111,0.001573529,0.6817887],"study_design_scores_gemma":[0.0002809642,0.001786925,0.03940645,0.00006773717,0.0002100445,0.003198493,0.0002774778,0.3409202,0.599676,0.009499873,0.004605654,0.00007025305],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.7915818,0.0005261603,0.2037488,0.0003698018,0.00009488368,0.0000311553,0.0001074781,0.0002733686,0.003266536],"genre_scores_gemma":[0.9743457,0.0001761383,0.02335447,0.00002169806,0.00002465682,0.00000814057,0.00003982813,0.0000184618,0.002010882],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.002394733,"threshold_uncertainty_score":0.008011162,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01158009423492415,"score_gpt":0.244802512093819,"score_spread":0.2332224178588948,"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."}}