{"id":"W1522470493","doi":"10.1007/11559573_85","title":"Color Indexing by Nonparametric Statistics","year":2005,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Image Retrieval and Classification Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Queen's University","funders":"","keywords":"Histogram; Nonparametric statistics; Color histogram; Pattern recognition (psychology); Computer science; Robustness (evolution); Kernel density estimation; Artificial intelligence; Search engine indexing; Color space; Mathematics; Kernel method; Kernel (algebra); Algorithm; Statistics; Color image; Estimator; Support vector machine; 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":[0.00105316,0.0005699872,0.001493484,0.002239956,0.000642383,0.002149196,0.00131512,0.0006202491,0.007587259],"category_scores_gemma":[0.003491025,0.0005263464,0.0009083273,0.004080761,0.001211965,0.002776343,0.001670706,0.001538088,0.003749111],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008159908,"about_ca_system_score_gemma":0.0008611574,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001838795,"about_ca_topic_score_gemma":0.00249216,"domain_scores_codex":[0.9991719,0.0002371568,0.00004193801,0.0001642186,0.0003097449,0.00007521958],"domain_scores_gemma":[0.9985681,0.0004158835,0.00009157642,0.0006050625,0.000271354,0.0000479717],"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":[0.0001527686,0.00007137194,0.0003882259,0.0001411725,0.00004622732,0.00003520232,0.00004731085,0.02903071,0.01321626,0.1830347,0.01424051,0.7595955],"study_design_scores_gemma":[0.00002172104,0.00004916431,0.0007273749,0.00002579097,0.00002945405,0.0002240311,0.0000300048,0.6999665,0.01317211,0.2655786,0.02012321,0.00005197017],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002017453,0.0005003822,0.9934616,0.00005985259,0.00005516025,0.00001729688,0.0001145196,0.001209612,0.002564105],"genre_scores_gemma":[0.1263734,0.001377935,0.8544882,0.0001544857,0.0002560109,0.0001516163,0.001149921,0.0009181242,0.01513026],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.007587259,"threshold_uncertainty_score":0.02538192,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01536051187205489,"score_gpt":0.25860551573421,"score_spread":0.2432450038621551,"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."}}