{"id":"W2296434085","doi":"10.1109/icip.2015.7351694","title":"Adaptive exposure fusion for high dynamic range imaging","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":"Toronto Metropolitan University","funders":"","keywords":"High dynamic range; Fusion; Computer science; Image fusion; Artificial intelligence; High-dynamic-range imaging; Dynamic range; Image (mathematics); Computer vision; Human visual system model; Range (aeronautics); Perception; 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":[0.0003009736,0.00009899777,0.00009611621,0.00007097737,0.00005153927,0.00007899588,0.0004995147,0.00002393612,0.00001172226],"category_scores_gemma":[0.00002385034,0.00008458446,0.00003144192,0.0001317967,0.0000197615,0.0006499176,0.0002222017,0.00004770458,0.0000299051],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008001934,"about_ca_system_score_gemma":0.00004018936,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003609886,"about_ca_topic_score_gemma":0.00001422602,"domain_scores_codex":[0.9991835,0.00002414339,0.0001242508,0.0002688148,0.0001900012,0.0002093214],"domain_scores_gemma":[0.999345,0.00003388544,0.00004651342,0.0003514618,0.0001640017,0.000059142],"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":[0.00009171932,0.0002230854,0.0007261562,0.0000344145,0.0000265472,0.00004017745,0.002145136,0.00001578596,0.0252059,0.1876261,0.1160774,0.6677876],"study_design_scores_gemma":[0.003351578,0.001141447,0.001364561,0.00007953331,0.00001660469,0.00002614757,0.000342766,0.6800575,0.1683347,0.1305041,0.01377552,0.001005503],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002182093,0.00009938318,0.9910218,0.001126883,0.0002823893,0.0003584312,0.000001718317,0.000684099,0.004243203],"genre_scores_gemma":[0.5695397,0.000001887632,0.4281101,0.0003458729,0.00002374419,0.00005519339,0.000001951001,0.000006463343,0.001915155],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6800417,"threshold_uncertainty_score":0.3449254,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01929153986927212,"score_gpt":0.2628638592240528,"score_spread":0.2435723193547807,"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."}}