{"id":"W4205987915","doi":"10.3390/app12031051","title":"Semantic Segmentation Based on Depth Background Blur","year":2022,"lang":"en","type":"article","venue":"Applied Sciences","topic":"Advanced Neural Network Applications","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Segmentation; Pascal (unit); Artificial intelligence; Convolutional neural network; Inference; Pattern recognition (psychology); Fuzzy inference system; Focus (optics); Image segmentation; Fuzzy logic; Adaptive neuro fuzzy inference system; Fuzzy control system","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":[],"consensus_categories":[],"category_scores_codex":[0.0003992643,0.0001112953,0.00008969753,0.0001292998,0.001288254,0.0001346507,0.001262711,0.0000128112,0.00006590705],"category_scores_gemma":[0.000003907821,0.0001048515,0.00003036691,0.001604062,0.0001345107,0.0002157079,0.0002662075,0.0001409672,0.00009928861],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007526908,"about_ca_system_score_gemma":0.00007775479,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004415929,"about_ca_topic_score_gemma":0.00000555853,"domain_scores_codex":[0.9982746,0.00004902116,0.0001584825,0.000568783,0.0006608861,0.0002882355],"domain_scores_gemma":[0.9991884,0.0002258672,0.0001043484,0.0004062573,0.00001327962,0.00006189167],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000009021012,0.0001537801,0.0003003583,0.000004503678,0.000003317225,0.000004227718,0.000221566,0.4297111,0.0119568,0.517989,0.001894592,0.03775176],"study_design_scores_gemma":[0.0005601749,0.0003556033,0.002142298,0.000004572422,0.000006798406,0.00001055202,0.0005722813,0.9378505,0.01042392,0.03893191,0.008663244,0.0004781477],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04695218,0.00002396452,0.9147667,0.002756214,0.000310714,0.0005717466,0.000002460051,0.0003286497,0.03428736],"genre_scores_gemma":[0.9367036,0.000001264739,0.06027593,0.002566853,0.00003324764,0.0003122291,0.000004139261,0.00000552074,0.00009726283],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8897514,"threshold_uncertainty_score":0.9908338,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03967018903237247,"score_gpt":0.2926895184385241,"score_spread":0.2530193294061516,"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."}}