{"id":"W3164119733","doi":"10.18280/ria.350210","title":"MODFAT: Moving Object Detection by Removing Shadow Based on Fuzzy Technique with an Adaptive Thresholding Method","year":2021,"lang":"en","type":"article","venue":"Revue d intelligence artificielle","topic":"Video Surveillance and Tracking Methods","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Artificial intelligence; Computer vision; Shadow (psychology); Thresholding; Computer science; Object detection; Object (grammar); Fuzzy logic; Projection (relational algebra); Segmentation; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.002120184,0.0003206435,0.0003601134,0.0002136529,0.0004307435,0.0003225842,0.0007221132,0.0001551637,0.00002722409],"category_scores_gemma":[0.000270512,0.0003052374,0.0001268553,0.001445561,0.00005659833,0.0006565136,0.0001346928,0.0005039424,0.00002996065],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001408423,"about_ca_system_score_gemma":0.0001329098,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001219996,"about_ca_topic_score_gemma":0.0001017175,"domain_scores_codex":[0.9968467,0.0006211197,0.0004412752,0.001152792,0.0003940819,0.0005440349],"domain_scores_gemma":[0.9973956,0.0006543564,0.0002019204,0.001308511,0.0002795477,0.0001600559],"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":[0.0001051795,0.0002475834,0.0001776836,0.00004872385,0.00002554164,0.0001774543,0.000645597,0.2834762,0.1644747,0.005375328,0.0000256526,0.5452203],"study_design_scores_gemma":[0.00003407143,0.0003478401,0.00002804341,0.0001347123,0.000005501165,0.00005997573,0.000160451,0.52211,0.4741938,0.002541466,0.0001458992,0.0002382424],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002912171,0.0001483099,0.9915848,0.0002640061,0.000223406,0.0003250479,0.000004963323,0.0003771536,0.004160163],"genre_scores_gemma":[0.5918851,0.000009911432,0.4076058,0.0002708893,0.00005330087,0.00004957406,0.000004485882,0.00002716612,0.00009381164],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5889729,"threshold_uncertainty_score":0.99994,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04121119767389284,"score_gpt":0.3049259772683708,"score_spread":0.263714779594478,"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."}}