{"id":"W2061261185","doi":"10.1109/icce.2015.7066441","title":"A new hybrid tone mapping scheme for high dynamic range (HDR) videos","year":2015,"lang":"en","type":"article","venue":"","topic":"Image Enhancement Techniques","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Telus (Canada); University of British Columbia","funders":"","keywords":"Tone mapping; High dynamic range; Computer science; Frame (networking); Scheme (mathematics); Computer vision; Flicker; Tone (literature); Artificial intelligence; Dynamic range; Range (aeronautics); Computer graphics (images); Mathematics; Engineering; Telecommunications","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003600065,0.000145799,0.0001687813,0.0001169444,0.00005046957,0.000153353,0.000819926,0.00003272917,0.0000387715],"category_scores_gemma":[0.00006400979,0.0001357748,0.00005194313,0.0002156072,0.00001648939,0.0007471533,0.0003075229,0.00007058607,0.0001071171],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001181095,"about_ca_system_score_gemma":0.0001303276,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001830209,"about_ca_topic_score_gemma":0.00001733114,"domain_scores_codex":[0.9987894,0.00001888265,0.0002181957,0.0003775057,0.0002592867,0.0003367141],"domain_scores_gemma":[0.9990416,0.00004276036,0.00006931109,0.000574598,0.0001281216,0.0001436652],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0000334074,0.0001206408,0.0001024193,0.00006572728,0.00005550297,0.00003812919,0.0006907571,0.000005146418,0.04012886,0.1079717,0.5672038,0.2835839],"study_design_scores_gemma":[0.003994307,0.0006746249,0.0003431945,0.0001414747,0.00001629458,0.00005889275,0.00006840046,0.2223873,0.5343879,0.08632062,0.1503372,0.001269789],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002309625,0.00009948471,0.9900007,0.002156206,0.0002681485,0.0005329396,0.000001689037,0.00100887,0.003622297],"genre_scores_gemma":[0.1344151,0.000004276475,0.8557274,0.000798824,0.00007792996,0.00007770023,0.000005797973,0.00001358434,0.008879418],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.494259,"threshold_uncertainty_score":0.5536736,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0277749760674757,"score_gpt":0.2907689895672202,"score_spread":0.2629940134997445,"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."}}