{"id":"W3216658279","doi":"10.18280/ts.380504","title":"Color Based Object Categorization Using Histograms of Oriented Hue and Saturation","year":2021,"lang":"en","type":"article","venue":"Traitement du signal","topic":"Industrial Vision Systems and Defect Detection","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Artificial intelligence; Hue; Histogram; Pattern recognition (psychology); Luminance; Chrominance; Computer vision; Computer science; Cognitive neuroscience of visual object recognition; Support vector machine; Categorization; Invariant (physics); Color space; Object (grammar); Mathematics; Image (mathematics)","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":[0.0003610441,0.0003063748,0.000429171,0.002618844,0.0001661073,0.0007336438,0.0003423985,0.0002798081,0.001223031],"category_scores_gemma":[0.0007187917,0.0001305601,0.0004347558,0.001500026,0.0004131061,0.0008871222,0.0004517688,0.0002508285,0.0006919852],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003307318,"about_ca_system_score_gemma":0.0003035071,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002212109,"about_ca_topic_score_gemma":0.001508731,"domain_scores_codex":[0.9996952,0.00003057155,0.0000152783,0.00006125963,0.0001471147,0.00005073092],"domain_scores_gemma":[0.9996763,0.00006216497,0.0000429973,0.00003831713,0.000149124,0.00003105998],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003384104,0.0001649359,0.008296062,0.0002548357,0.0001127091,0.0001287646,0.0001086405,0.01471141,0.1699923,0.004849677,0.003989134,0.7970532],"study_design_scores_gemma":[0.00007652432,0.000657454,0.08334035,0.00009725706,0.0001930284,0.001289268,0.000546667,0.6741595,0.2003816,0.01932597,0.01970697,0.0002254401],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2161138,0.002112749,0.7680249,0.000212073,0.0002681424,0.0001702054,0.0007283491,0.002855103,0.009514628],"genre_scores_gemma":[0.8946179,0.0007972005,0.1007455,0.0001150738,0.0001296965,0.0000586019,0.0007936512,0.0001064689,0.002636037],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002618844,"threshold_uncertainty_score":0.004398465,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01726435118149542,"score_gpt":0.2145602435217408,"score_spread":0.1972958923402454,"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."}}