{"id":"W2792035262","doi":"10.1049/iet-ipr.2017.0232","title":"Effect of fusing features from multiple DCNN architectures in image classification","year":2018,"lang":"en","type":"article","venue":"IET Image Processing","topic":"Advanced Neural Network Applications","field":"Computer Science","cited_by":47,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"","keywords":"Artificial intelligence; Computer science; Contextual image classification; Pattern recognition (psychology); Image (mathematics); Computer vision","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":[0.001256792,0.001515847,0.0008274178,0.0006915195,0.000356988,0.0005930928,0.0007122709,0.0009854223,0.001092681],"category_scores_gemma":[0.003642332,0.0004225494,0.0008099686,0.0006057991,0.0005110625,0.00207955,0.001343846,0.0009628067,0.000345819],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005508164,"about_ca_system_score_gemma":0.0005339157,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002568915,"about_ca_topic_score_gemma":0.002600338,"domain_scores_codex":[0.9993439,0.00009885199,0.00004678597,0.000165411,0.0001935388,0.0001513898],"domain_scores_gemma":[0.9990233,0.0003300899,0.0001063504,0.0001825666,0.0002757189,0.00008196279],"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":[0.0009335529,0.0004866423,0.005627932,0.000173717,0.0002878268,0.0003663087,0.0001804885,0.2701708,0.1000474,0.001545751,0.001507383,0.6186722],"study_design_scores_gemma":[0.00002625316,0.0007011376,0.005691319,0.0000352855,0.0002191983,0.00022456,0.00009099734,0.9266937,0.06274255,0.00190871,0.001625161,0.00004101274],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7396902,0.00202345,0.2498524,0.0005158607,0.0003396178,0.00008970426,0.0001212724,0.002408569,0.004958735],"genre_scores_gemma":[0.9551187,0.0001790157,0.04351191,0.0001035111,0.00002770344,0.0000278176,0.0001192261,0.00005603234,0.000856088],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002568915,"threshold_uncertainty_score":0.006646633,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01241567911412153,"score_gpt":0.2999108926474271,"score_spread":0.2874952135333055,"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."}}