{"id":"W1709676693","doi":"","title":"Non-linear normalized entropy based exposure blending","year":2013,"lang":"en","type":"article","venue":"Graphics Interface","topic":"Image Enhancement Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Tone mapping; Normalization (sociology); Dynamic range; Classification of discontinuities; Entropy (arrow of time); High dynamic range; High-dynamic-range imaging; Computer science; Dynamic range compression; Linearity; Radiometry; Artificial intelligence; Computer vision; Irradiance; Algorithm; Mathematics; Optics; Physics; Engineering; Electronic engineering","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":[0.0003056932,0.0002236438,0.0001972433,0.0002561363,0.000127827,0.0002454007,0.001346682,0.00009392711,0.0002163501],"category_scores_gemma":[0.00003545721,0.000210046,0.0001083253,0.0005348103,0.00007767763,0.0009187936,0.0003265738,0.0003006022,0.0003235906],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004216192,"about_ca_system_score_gemma":0.00003889826,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007136076,"about_ca_topic_score_gemma":0.000003661427,"domain_scores_codex":[0.9984004,0.00005703848,0.0003151885,0.0004373364,0.0003500854,0.0004399907],"domain_scores_gemma":[0.998666,0.0000646602,0.0001282603,0.0008537491,0.0001877655,0.00009958203],"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":[0.00005436025,0.000660411,0.009575323,0.0002351898,0.0001916825,0.00006580011,0.002203632,0.000562975,0.772629,0.1257878,0.06965607,0.01837783],"study_design_scores_gemma":[0.000541631,0.0002252993,0.0005175241,0.00008670486,0.000006676263,0.000005573802,0.00001962353,0.2571611,0.733794,0.002720464,0.004562763,0.0003586089],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04629448,0.00008305521,0.9498245,0.0008792821,0.000434491,0.0003986171,0.000001371932,0.0006436494,0.001440588],"genre_scores_gemma":[0.8506382,0.00002009563,0.1482154,0.0006421325,0.00004093629,0.00008847899,0.000002340085,0.00001776239,0.0003346371],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8043437,"threshold_uncertainty_score":0.8565428,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01413246175990532,"score_gpt":0.264718053958632,"score_spread":0.2505855921987267,"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."}}