{"id":"W2123851435","doi":"10.1109/iccv.2011.6126366","title":"Cluster-based color space optimizations","year":2011,"lang":"en","type":"article","venue":"","topic":"Image Enhancement Techniques","field":"Computer Science","cited_by":53,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Gamut; Color space; Computer science; Computer vision; Artificial intelligence; Grayscale; Computer graphics (images); Multispectral image; RGB color space; Color quantization; Color histogram; ICC profile; Color image; Color model; Image processing; Image (mathematics)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000498375,0.001041093,0.0008027309,0.0008235635,0.0006619006,0.0009546707,0.001292097,0.0005555096,0.004619248],"category_scores_gemma":[0.001527187,0.0003004994,0.0007699538,0.001178894,0.0005822417,0.0009394187,0.001321664,0.0008998823,0.000729584],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001130668,"about_ca_system_score_gemma":0.0008799587,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004054656,"about_ca_topic_score_gemma":0.005428689,"domain_scores_codex":[0.9995802,0.00007771674,0.00001529173,0.00008525548,0.0001723957,0.00006911143],"domain_scores_gemma":[0.9995338,0.00009615355,0.00002943568,0.0001166057,0.0001959817,0.00002802554],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002274484,0.0001234648,0.0008437987,0.0001047994,0.00007081526,0.00006119649,0.0001633765,0.7540907,0.0348849,0.05089893,0.00765716,0.1508733],"study_design_scores_gemma":[0.00001959328,0.00002945311,0.0002010552,0.000003289113,0.00001302315,0.00003723147,0.00003980242,0.9764863,0.007553872,0.01243984,0.003163811,0.00001269169],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03022731,0.0001501809,0.9597673,0.0001532446,0.00005389343,0.00006249715,0.00009537324,0.001207976,0.008282276],"genre_scores_gemma":[0.4585232,0.0001722747,0.5300762,0.0001255951,0.0000413395,0.0001795094,0.0002969068,0.001102573,0.009482335],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004619248,"threshold_uncertainty_score":0.01545292,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02795430871499295,"score_gpt":0.2364775980452846,"score_spread":0.2085232893302917,"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."}}