{"id":"W2073864116","doi":"10.5539/mas.v3n7p78","title":"Shadow Elimination Method for Video Surveillance","year":2009,"lang":"en","type":"article","venue":"Modern Applied Science","topic":"Video Surveillance and Tracking Methods","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Artificial intelligence; Computer vision; Computer science; Segmentation; Shadow (psychology); Color histogram; Image segmentation; Histogram; RGB color model; Region growing; Feature (linguistics); Pattern recognition (psychology); Color image; Image (mathematics); Scale-space segmentation; Image processing","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005140097,0.0001995084,0.0002593409,0.0002339924,0.0005092177,0.0004204902,0.001939508,0.00005490698,0.000002308808],"category_scores_gemma":[0.000249006,0.000186205,0.00007533915,0.001272316,0.0001293653,0.0006752092,0.0001352083,0.0001273961,0.00001866292],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008923684,"about_ca_system_score_gemma":0.0001924184,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006791343,"about_ca_topic_score_gemma":0.000008703644,"domain_scores_codex":[0.9973025,0.00006359105,0.0002922546,0.001015427,0.0006714562,0.0006547561],"domain_scores_gemma":[0.9982036,0.0003540109,0.0001527359,0.0008949686,0.0002427248,0.0001519165],"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":[0.00001237748,0.0000408481,0.00006112498,0.000006235673,0.000002171046,0.000001228709,0.0003683253,0.0006797916,0.1856541,0.1748808,0.0001120207,0.638181],"study_design_scores_gemma":[0.0003614009,0.00007896843,0.0163648,0.000005720044,0.000001842007,0.00000926051,0.000007211382,0.7420547,0.02628526,0.2134496,0.001089524,0.0002917222],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0007575725,0.00005429242,0.9889122,0.00177784,0.0002787893,0.0003994399,0.000002813373,0.0003158481,0.007501189],"genre_scores_gemma":[0.5416843,0.000002201781,0.4571257,0.001070588,0.00004628025,0.00002977182,9.902993e-7,0.000005062907,0.00003514939],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7413749,"threshold_uncertainty_score":0.7593221,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02168287510974554,"score_gpt":0.3229870883030282,"score_spread":0.3013042131932827,"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."}}