{"id":"W4390270970","doi":"10.18280/ria.370607","title":"Randomized Information Hiding in RGB Images Using Genetic Algorithm and Huffman Coding","year":2023,"lang":"en","type":"article","venue":"Revue d intelligence artificielle","topic":"Advanced Data Compression Techniques","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Huffman coding; Computer science; Coding (social sciences); Tunstall coding; Artificial intelligence; Algorithm; RGB color model; Information hiding; Computer vision; Pattern recognition (psychology); Mathematics; Data compression; Image (mathematics); Statistics","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":[0.0002731682,0.0002844851,0.0003183636,0.0004714446,0.0002099409,0.0003455113,0.0003920732,0.0003906601,0.000691979],"category_scores_gemma":[0.0006267856,0.0001624909,0.000404841,0.0005402747,0.0003319954,0.0005328277,0.0002326815,0.0003304251,0.0001713294],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005622454,"about_ca_system_score_gemma":0.0005795692,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004249417,"about_ca_topic_score_gemma":0.003980977,"domain_scores_codex":[0.9997854,0.00004266649,0.000008910622,0.00003164119,0.0001102359,0.00002118501],"domain_scores_gemma":[0.9998401,0.00006160769,0.00002907808,0.00002039628,0.00004388122,0.000004919305],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002688563,0.0001432888,0.001440601,0.000231069,0.00009396794,0.0002450183,0.0002709834,0.4678013,0.1463056,0.0221831,0.001014279,0.360002],"study_design_scores_gemma":[0.00001531318,0.0000959602,0.0006201142,0.00001777336,0.0000209302,0.0001414883,0.0000251012,0.9592773,0.0360128,0.002422686,0.001331857,0.00001859112],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.07405516,0.0005615139,0.9203587,0.0001556644,0.00004125521,0.00006453416,0.00003758559,0.0007725183,0.003953095],"genre_scores_gemma":[0.5195479,0.0005618527,0.4762029,0.00006195608,0.00001424313,0.0000800219,0.00007195563,0.0000435485,0.003415587],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004249417,"threshold_uncertainty_score":0.008449376,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04332665439721112,"score_gpt":0.3093418479414545,"score_spread":0.2660151935442434,"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."}}