{"id":"W2763247712","doi":"10.1111/cgf.13275","title":"ℒ0 Gradient‐Preserving Color Transfer","year":2017,"lang":"en","type":"article","venue":"Computer Graphics Forum","topic":"Image Enhancement Techniques","field":"Computer Science","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Artificial intelligence; Computer vision; Computer science; Palette (painting); Pixel; Color balance; Color histogram; Color image; Color quantization; High color; Similarity (geometry); Color normalization; Color depth; Image (mathematics); Pattern recognition (psychology); Image processing","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":[0.0001972219,0.0005063586,0.0003074431,0.0005523968,0.0002612578,0.0005835991,0.0008886708,0.0004030214,0.005375701],"category_scores_gemma":[0.0004379803,0.0002086942,0.0004141254,0.0005085507,0.0003758811,0.0008656716,0.0006045405,0.000701652,0.001698164],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003158624,"about_ca_system_score_gemma":0.0003560537,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009856184,"about_ca_topic_score_gemma":0.0007042449,"domain_scores_codex":[0.999798,0.00002442604,0.000007186238,0.00004582063,0.0001031696,0.00002136404],"domain_scores_gemma":[0.999833,0.00002313074,0.00001421195,0.00005145187,0.00006512641,0.00001310608],"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":[0.000291503,0.0001512233,0.0005017563,0.0001739756,0.00004829498,0.0001453427,0.00008965709,0.02403066,0.2550963,0.0127143,0.005607375,0.7011496],"study_design_scores_gemma":[0.00007132368,0.0002240011,0.001435308,0.00001482104,0.00004032221,0.0008151043,0.00003590069,0.6076218,0.3579714,0.007012657,0.02470356,0.0000537777],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02739585,0.0003279332,0.9632505,0.0001188145,0.0001429071,0.00007373841,0.00005157038,0.001680284,0.006958477],"genre_scores_gemma":[0.4491567,0.0005076334,0.5281764,0.0002225939,0.0001358323,0.0001004411,0.0002129763,0.0003290709,0.02115837],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005375701,"threshold_uncertainty_score":0.01798356,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02083667922678898,"score_gpt":0.262990408689435,"score_spread":0.242153729462646,"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."}}