{"id":"W4232452588","doi":"10.2139/ssrn.3949190","title":"Clothes Identification Using Inception ResNet V2 and MobileNet V2","year":2021,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Face recognition and analysis","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Lambton College","funders":"","keywords":"Identification (biology); Computer science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003790075,0.001251721,0.00064932,0.002344776,0.0003043944,0.0006256373,0.0008734867,0.0008941461,0.01124811],"category_scores_gemma":[0.0008344467,0.0002572322,0.0004882474,0.0008034295,0.0001846708,0.0007482183,0.0006850234,0.0003001224,0.004874802],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005207577,"about_ca_system_score_gemma":0.0005355038,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01326761,"about_ca_topic_score_gemma":0.01355874,"domain_scores_codex":[0.9997178,0.00003407536,0.00001771758,0.00007943057,0.00006990597,0.00008102479],"domain_scores_gemma":[0.9997745,0.00003374684,0.00001541328,0.00003809589,0.0001119647,0.00002640494],"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":[0.001924474,0.0008478768,0.01079517,0.0003943151,0.0002987501,0.0005834342,0.0001293861,0.02798325,0.0605483,0.001845019,0.05731542,0.8373347],"study_design_scores_gemma":[0.0001353524,0.0005752344,0.02150273,0.00005993548,0.0001263615,0.0006109054,0.0002468231,0.8655884,0.09089929,0.001980455,0.01817062,0.000103789],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5641512,0.001851456,0.2632287,0.0006868583,0.001377565,0.0009633886,0.02132738,0.1147565,0.03165688],"genre_scores_gemma":[0.8300615,0.0004032486,0.1191733,0.0005243003,0.0001825156,0.0005048233,0.0233667,0.001091563,0.02469199],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01326761,"threshold_uncertainty_score":0.03762871,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0126894191518953,"score_gpt":0.251715638213765,"score_spread":0.2390262190618697,"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."}}