{"id":"W3013947696","doi":"10.18280/isi.250111","title":"Performance Evaluation of Generative Adversarial Networks for Computer Vision Applications","year":2020,"lang":"en","type":"article","venue":"Ingénierie des systèmes d information","topic":"Advanced Image Processing Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Adversarial system; Generative grammar; Computer science; Artificial intelligence; Generative adversarial network; Computer vision; Human–computer interaction; Machine learning; Deep learning","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005848307,0.0001277631,0.0001642015,0.00009532773,0.0002143135,0.0001458281,0.0004305381,0.00007252338,0.000002769297],"category_scores_gemma":[0.0001022272,0.0001268054,0.00005025505,0.000448596,0.00007925004,0.004903307,0.0001334721,0.0000776378,0.000006161659],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001370673,"about_ca_system_score_gemma":0.0001269865,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001546462,"about_ca_topic_score_gemma":2.559844e-7,"domain_scores_codex":[0.9987807,0.00005111702,0.000487695,0.0001678388,0.0003467444,0.0001658814],"domain_scores_gemma":[0.9980914,0.0000563193,0.0004302917,0.0002348461,0.001131123,0.00005600508],"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":[0.00003663871,0.00001574373,0.00005175203,0.00017188,0.0000140951,3.564539e-8,0.00264259,0.07070164,0.0006240199,0.003965681,0.0005237779,0.9212521],"study_design_scores_gemma":[0.0004409615,0.0002430873,0.0002579677,0.00005152426,0.00001552853,0.000002412098,0.00002881024,0.991607,0.003630928,0.002480398,0.001108512,0.000132837],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002146006,0.00006043598,0.9956874,0.0001401917,0.0001137237,0.001057369,0.000006461868,0.0002622214,0.0005262159],"genre_scores_gemma":[0.5067287,0.000008915985,0.4926234,0.000213352,0.0001083771,0.0002656959,0.00004613785,0.000004623054,8.201528e-7],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9211193,"threshold_uncertainty_score":0.5170975,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02596047291657484,"score_gpt":0.285848169300868,"score_spread":0.2598876963842932,"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."}}