{"id":"W4360989186","doi":"10.18280/ria.370124","title":"Image Counterfeiting Detection and Localization Using Deep Learning Algorithms","year":2023,"lang":"en","type":"article","venue":"Revue d intelligence artificielle","topic":"Digital Media Forensic Detection","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Artificial intelligence; Computer science; Deep learning; Image (mathematics); Computer vision; Pattern recognition (psychology); Algorithm","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":[0.0009109353,0.001532558,0.001079035,0.002230186,0.0003838912,0.001140013,0.001826416,0.001481435,0.001414586],"category_scores_gemma":[0.002098168,0.0004611748,0.0008421903,0.001179059,0.0005175965,0.00120468,0.001039195,0.001493174,0.001102337],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001377351,"about_ca_system_score_gemma":0.001033166,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01035783,"about_ca_topic_score_gemma":0.008993954,"domain_scores_codex":[0.9994079,0.00009332167,0.00003598921,0.000171993,0.000166509,0.0001242134],"domain_scores_gemma":[0.9993159,0.000181069,0.0001016573,0.0001160549,0.0002454632,0.00003992113],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003506039,0.0004156843,0.003346263,0.0001154999,0.0001179933,0.0001871647,0.00006336577,0.2232891,0.01026594,0.002191284,0.008076431,0.7515807],"study_design_scores_gemma":[0.000006560315,0.00003319513,0.0003989268,0.00001085484,0.00001036367,0.00003538507,0.00001620386,0.9936718,0.004073564,0.0011502,0.0005868855,0.000006117441],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1793939,0.003300963,0.8015082,0.001032612,0.0001829785,0.0002120728,0.0008391022,0.007680683,0.005849436],"genre_scores_gemma":[0.7444913,0.001059776,0.2426808,0.0004467633,0.0001056238,0.0001315046,0.002579364,0.0001273894,0.008377471],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01035783,"threshold_uncertainty_score":0.02059507,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03027157267377261,"score_gpt":0.2656719639298126,"score_spread":0.23540039125604,"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."}}