{"id":"W2107154924","doi":"10.1109/icip.2005.1529840","title":"Localization and security enhancement of block-based image authentication","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced Steganography and Watermarking Techniques","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Computer science; Vector quantization; Digital watermarking; Block (permutation group theory); Authentication (law); Computer vision; Image (mathematics); Artificial intelligence; Quantization (signal processing); Cryptography; Watermark; Pattern recognition (psychology); Mathematics; Algorithm; Computer security","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":[0.0003262445,0.0002813664,0.0003260231,0.0003666574,0.000181613,0.0002903803,0.0002831557,0.0005250989,0.001820406],"category_scores_gemma":[0.001484213,0.0001752654,0.0001984571,0.0003630091,0.000371777,0.0009482476,0.0005757018,0.0003361001,0.001049017],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001741452,"about_ca_system_score_gemma":0.000288166,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002160611,"about_ca_topic_score_gemma":0.000203459,"domain_scores_codex":[0.9995807,0.000111337,0.00002167103,0.00005372775,0.0001869595,0.00004556476],"domain_scores_gemma":[0.9990714,0.0003188143,0.0001514763,0.0001984765,0.000225191,0.00003466125],"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":[0.000609621,0.00006179418,0.0007508491,0.0001902388,0.00002756429,0.0002900208,0.0001248483,0.03309152,0.7177576,0.02053928,0.0008932828,0.2256633],"study_design_scores_gemma":[0.00006441014,0.0008047184,0.001482595,0.00003524628,0.00004376117,0.001843252,0.00005546087,0.560122,0.4138784,0.009073927,0.01255261,0.0000435901],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1385043,0.001265982,0.8540539,0.0002932691,0.00008443034,0.00004956965,0.00003078381,0.0007340995,0.00498375],"genre_scores_gemma":[0.8682369,0.0007330158,0.1275861,0.00006088354,0.00005928318,0.0000293725,0.00005264575,0.0000290915,0.003212746],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001820406,"threshold_uncertainty_score":0.006089866,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006885165410079029,"score_gpt":0.2450756086373221,"score_spread":0.238190443227243,"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."}}