{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003639591,0.000395747,0.0004414626,0.0008414934,0.0002323148,0.0006599906,0.0005765386,0.0004906197,0.004261372],"category_scores_gemma":[0.0007755122,0.0002207379,0.0004959062,0.0006334501,0.0002700432,0.001008324,0.0005716716,0.0006440424,0.001365851],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002483774,"about_ca_system_score_gemma":0.0002773685,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004661326,"about_ca_topic_score_gemma":0.0007368739,"domain_scores_codex":[0.9995818,0.00004209742,0.00002934096,0.0000987241,0.0001993529,0.00004873988],"domain_scores_gemma":[0.9996753,0.00007101594,0.00003555221,0.00004254335,0.000163706,0.00001195188],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003195984,0.0001576957,0.001243795,0.0005161309,0.00009516631,0.0003072147,0.0001378761,0.01064055,0.4307507,0.005688665,0.004554544,0.5455882],"study_design_scores_gemma":[0.00004743365,0.0003913161,0.006127892,0.00006717831,0.0001048682,0.001781806,0.00009306065,0.2254891,0.7249605,0.002386995,0.03845663,0.00009318455],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02838452,0.001010418,0.9619715,0.0001545929,0.000140527,0.000138028,0.0001142672,0.001442183,0.006643955],"genre_scores_gemma":[0.3193504,0.00179358,0.6595116,0.0002269551,0.0001039851,0.0001544597,0.0003792793,0.0001558299,0.01832398],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004261372,"threshold_uncertainty_score":0.0142557,"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."}}