{"id":"W2369846938","doi":"","title":"Overview of Digital Image Watermarking Algorithm Robust to Geometric Attacks","year":2009,"lang":"en","type":"article","venue":"Microcomputer applications","topic":"Simulation and Modeling Applications","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Digital watermarking; Computer science; Robustness (evolution); Feature (linguistics); Artificial intelligence; Computer vision; Image (mathematics); Algorithm; Transformation geometry; Feature selection; Digital image; Image processing","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.0004438888,0.0006093314,0.0006173592,0.00205641,0.0003378673,0.000939277,0.0005709167,0.0009432251,0.002113339],"category_scores_gemma":[0.0008386229,0.0003065717,0.0006146948,0.001462604,0.0003267194,0.0014443,0.0003911992,0.0007030553,0.001372345],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000362559,"about_ca_system_score_gemma":0.0004992204,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006597922,"about_ca_topic_score_gemma":0.0004099098,"domain_scores_codex":[0.9995827,0.00003852176,0.00005206697,0.0000943232,0.0001971801,0.00003519972],"domain_scores_gemma":[0.9997573,0.00004536801,0.0000272884,0.00003405969,0.0001251864,0.00001077473],"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":[0.0002273519,0.00004913798,0.0006351814,0.0006044729,0.00006015741,0.0002153835,0.00013639,0.01755399,0.07215793,0.03461612,0.004602222,0.8691417],"study_design_scores_gemma":[0.0001306506,0.0006819787,0.002725312,0.000265289,0.0001859975,0.004087672,0.0001324336,0.4973836,0.2159967,0.03363733,0.2445657,0.0002073091],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.007392863,0.009897471,0.9728084,0.0002764172,0.0003232527,0.0001137291,0.00009823792,0.001342626,0.007746899],"genre_scores_gemma":[0.1203102,0.01729982,0.8414474,0.0002172081,0.0005873349,0.0002453448,0.0006974209,0.0001518636,0.01904346],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002113339,"threshold_uncertainty_score":0.007069826,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02660837617565766,"score_gpt":0.2719717976659963,"score_spread":0.2453634214903387,"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."}}