{"id":"W7134097774","doi":"","title":"Généralisation de domaine en vision par ordinateur : apport des modèles pré-entraînés à grande échelle","year":2025,"lang":"fr","type":"dissertation","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Domain Adaptation and Few-Shot Learning","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Exploit; Robustness (evolution); Domain adaptation; Training set; Focus (optics); Domain (mathematical analysis); Task (project management); Generalization","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":[0.001960974,0.001362014,0.001060163,0.0009241884,0.0003309421,0.001645844,0.001461116,0.001761509,0.00153176],"category_scores_gemma":[0.004783179,0.0005813406,0.001529855,0.0008499066,0.0007744067,0.002393638,0.00134852,0.003121021,0.00152044],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009309084,"about_ca_system_score_gemma":0.0008628117,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01039518,"about_ca_topic_score_gemma":0.008126058,"domain_scores_codex":[0.999321,0.0001629195,0.00002477964,0.0003017699,0.0001098012,0.0000796851],"domain_scores_gemma":[0.9987179,0.0007088811,0.00006873099,0.00024106,0.0002008657,0.0000626213],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003167639,0.0002057124,0.003796825,0.0001718934,0.0001620971,0.0001970305,0.0002669323,0.593194,0.01646284,0.00527456,0.004247771,0.3757035],"study_design_scores_gemma":[0.000005747915,0.00002778181,0.0005701418,0.00001190374,0.00001109917,0.00004793048,0.00002909674,0.9925246,0.002783894,0.003023954,0.0009539995,0.000009823751],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.08757948,0.001352335,0.9055034,0.0005787595,0.000131458,0.00009544958,0.0003154922,0.002779932,0.001663747],"genre_scores_gemma":[0.7405881,0.00113142,0.248922,0.0004352968,0.0001538841,0.0001535938,0.001638039,0.0004936855,0.006483872],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01039518,"threshold_uncertainty_score":0.02066934,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01682182157664572,"score_gpt":0.2470826615756214,"score_spread":0.2302608399989757,"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."}}