{"id":"W4226049128","doi":"10.1109/tip.2022.3162961","title":"Universal Background Subtraction Based on Arithmetic Distribution Neural Network","year":2022,"lang":"en","type":"article","venue":"IEEE Transactions on Image Processing","topic":"Video Surveillance and Tracking Methods","field":"Computer Science","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Histogram; Computer science; Artificial neural network; Subtraction; Artificial intelligence; Convolutional neural network; Algorithm; Probability distribution; Pattern recognition (psychology); Arithmetic; Mathematics; Image (mathematics); Statistics","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":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0007021509,0.0001998191,0.0001732939,0.0001481075,0.001521809,0.0003427803,0.0004152049,0.00004790694,0.00005745041],"category_scores_gemma":[0.000006353349,0.0002198227,0.0001217741,0.001156905,0.00005791908,0.0008664588,0.000005006956,0.0006611475,0.00001551452],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003107204,"about_ca_system_score_gemma":0.0001541589,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002596341,"about_ca_topic_score_gemma":0.000007721744,"domain_scores_codex":[0.9979763,0.0003858071,0.0002338643,0.0005138072,0.0004941907,0.0003960415],"domain_scores_gemma":[0.9990836,0.0002316055,0.000134508,0.0003751406,0.00009068445,0.00008445034],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001095965,0.0002947536,0.0000309319,0.00002641411,0.00001039012,0.00004208185,0.00008263373,0.6656963,0.0006940193,0.00008917837,0.0001405387,0.3327832],"study_design_scores_gemma":[0.0005866421,0.0002898317,0.0007967631,0.00003034579,0.0000212182,0.00004247895,0.00007024218,0.9936824,0.002754459,0.0003499355,0.001091452,0.0002842526],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005651127,0.00003359393,0.9913927,0.0008656096,0.001195234,0.0001456674,0.00002238151,0.0003649506,0.0003286945],"genre_scores_gemma":[0.9610762,0.000002992673,0.0382377,0.0004336033,0.00008063634,0.00004430747,0.00001412033,0.00002053115,0.00008992159],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9554251,"threshold_uncertainty_score":0.9997781,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02486213111972385,"score_gpt":0.2792896840390449,"score_spread":0.2544275529193211,"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."}}