{"id":"W3142983592","doi":"","title":"2 - Utilisation de la transformée de Fourier-Mellin pour la reconnaissance de formes multi-orientées et multi-échelles : application à l'analyse automatique de documents techniques","year":2001,"lang":"fr","type":"article","venue":"Traitement du signal","topic":"Handwritten Text Recognition Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Artificial intelligence; Pattern recognition (psychology); Fourier transform; Invariant (physics); Set (abstract data type); Mathematics","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00557357,0.0005692134,0.000463914,0.0003731977,0.000353114,0.0005877266,0.000874135,0.0005792473,0.000300821],"category_scores_gemma":[0.0001428449,0.0006392275,0.0003159333,0.0005556538,0.0003679737,0.001568073,0.00008713697,0.0006185571,0.00003645651],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009226833,"about_ca_system_score_gemma":0.0008678654,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001051694,"about_ca_topic_score_gemma":0.0002426311,"domain_scores_codex":[0.9949169,0.001728609,0.0009965834,0.000789583,0.0004758532,0.001092441],"domain_scores_gemma":[0.9977368,0.0006571946,0.0004577399,0.0004575373,0.000273083,0.0004177074],"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":[0.0001180664,0.002660608,0.01343542,0.0004632495,0.0003241892,0.0001323321,0.02083957,0.0006330599,0.07745266,0.01737693,0.002295758,0.8642682],"study_design_scores_gemma":[0.001584968,0.0002099898,0.006282518,0.0005963951,0.0001847835,0.0003676113,0.000410271,0.5882608,0.3536909,0.02098133,0.02671146,0.0007188939],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07071477,0.0007132931,0.9208485,0.003922706,0.00004706712,0.001275714,0.00004879006,0.0009823749,0.001446727],"genre_scores_gemma":[0.5170429,0.001926774,0.4786509,0.000713117,0.000114254,0.0008323488,0.00004080289,0.00004897645,0.0006298984],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8635493,"threshold_uncertainty_score":0.9996059,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03040789133369996,"score_gpt":0.3244224327595335,"score_spread":0.2940145414258335,"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."}}