{"id":"W3145991252","doi":"10.18280/isi.260110","title":"Image Pixel Contrast Enhancement Using Enhanced Multi Histogram Equalization Method","year":2021,"lang":"en","type":"article","venue":"Ingénierie des systèmes d information","topic":"Image Enhancement Techniques","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Histogram equalization; Artificial intelligence; Computer science; Computer vision; Contrast (vision); Histogram; Pixel; Adaptive histogram equalization; Brightness; Equalization (audio); Image (mathematics); Image enhancement; Pattern recognition (psychology); Channel (broadcasting)","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0007692978,0.0002668745,0.0002985159,0.0002612825,0.0003419328,0.0007465609,0.0004901281,0.0001185061,0.00006847028],"category_scores_gemma":[0.0003630184,0.0002930992,0.00009884288,0.0008247662,0.00008368259,0.007260463,0.0002764892,0.0001428001,0.00007875368],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007232919,"about_ca_system_score_gemma":0.0002338543,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005043466,"about_ca_topic_score_gemma":0.000008441903,"domain_scores_codex":[0.9976664,0.0002163306,0.0008748025,0.000312318,0.0004723948,0.0004577136],"domain_scores_gemma":[0.9977818,0.00006971804,0.0005227001,0.0006071445,0.0009278383,0.00009076832],"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":[0.00001062255,0.0001022174,0.00001428789,0.0002424092,0.00004031989,0.000005849755,0.006664553,0.0001715796,0.745159,0.009372455,0.0002160286,0.2380006],"study_design_scores_gemma":[0.0004904615,0.00005769113,0.00007425435,0.0001541409,0.00001534483,0.00002930334,0.000270109,0.2686671,0.7262824,0.001424821,0.00219117,0.0003431479],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.004799573,0.000123632,0.9893385,0.00004376437,0.0005084361,0.0004633222,0.000006072794,0.0006070728,0.004109602],"genre_scores_gemma":[0.2436971,0.00003273236,0.7555674,0.0003821344,0.00003575793,0.00008591598,0.00008273014,0.00001288937,0.0001033162],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.2684955,"threshold_uncertainty_score":0.9999521,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02623312701486845,"score_gpt":0.3024046900273754,"score_spread":0.2761715630125069,"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."}}