{"id":"W4388235934","doi":"10.1109/airc57904.2023.10303221","title":"Decentralized Federated Deep Learning Image Recognition Models","year":2023,"lang":"en","type":"article","venue":"","topic":"Privacy-Preserving Technologies in Data","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Deep learning; Server; Artificial intelligence; Software deployment; Image segmentation; Information privacy; Machine learning; Edge device; Data modeling; Object detection; Big data; Segmentation; Analytics; Federated learning; Data mining; Cloud computing; Computer security; Computer network; Database; Operating 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00122832,0.0006693274,0.001075627,0.0004132887,0.0004684944,0.001092602,0.002014659,0.00140821,0.002137752],"category_scores_gemma":[0.00291404,0.0003267344,0.0006682618,0.000535276,0.0009529228,0.002278592,0.001115303,0.001491975,0.0005814215],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001652156,"about_ca_system_score_gemma":0.001801777,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007236195,"about_ca_topic_score_gemma":0.007754631,"domain_scores_codex":[0.9991769,0.0001174108,0.00003697952,0.0002977375,0.0001961745,0.0001748084],"domain_scores_gemma":[0.9989396,0.0002354933,0.00009556904,0.000402032,0.0002757487,0.00005153356],"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":[0.000205363,0.0001612537,0.000871931,0.0000308493,0.00003753663,0.00007135392,0.00004623439,0.893512,0.004115047,0.00972772,0.00277524,0.08844545],"study_design_scores_gemma":[0.000006018964,0.00001494464,0.00006145472,0.000001552219,0.000002596347,0.00001023273,0.000003941213,0.9953885,0.00126817,0.003012753,0.0002271413,0.000002735365],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.07800445,0.0002426329,0.9141048,0.0004906276,0.00008913469,0.00007630313,0.0002696423,0.003602403,0.003120077],"genre_scores_gemma":[0.9160794,0.00007940164,0.07930769,0.0002197543,0.00002774644,0.0001168191,0.0003580401,0.00005694057,0.003754193],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.007236195,"threshold_uncertainty_score":0.01438814,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05889390558715171,"score_gpt":0.2853029534028733,"score_spread":0.2264090478157216,"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."}}