{"id":"W2157339705","doi":"10.1109/icsmc.2004.1400798","title":"Airborne multi-spectral images registration through genetic algorithm","year":2005,"lang":"en","type":"article","venue":"","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Affine transformation; Image registration; Computer science; Computer vision; Artificial intelligence; Transformation (genetics); Context (archaeology); Matching (statistics); Representation (politics); Field (mathematics); Image (mathematics); Mathematics; Geography","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":[0.0004065153,0.0004492895,0.000515515,0.0006121157,0.0003113752,0.0005573815,0.0007503812,0.0007632527,0.0009083469],"category_scores_gemma":[0.0008820402,0.000236359,0.0005476288,0.0005348119,0.0004994979,0.0004728413,0.0005507336,0.0004874662,0.0002331256],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005276175,"about_ca_system_score_gemma":0.0008414865,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004727921,"about_ca_topic_score_gemma":0.002931745,"domain_scores_codex":[0.9997868,0.00005794869,0.000006383966,0.00005881591,0.00006393083,0.00002610834],"domain_scores_gemma":[0.9998164,0.00008400191,0.00003155586,0.00002458103,0.00003324481,0.00001030304],"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":[0.00004367877,0.00006450596,0.0005925184,0.0000313451,0.0000361246,0.00005969895,0.0000689807,0.8883337,0.006435671,0.01260861,0.0003400503,0.09138513],"study_design_scores_gemma":[0.00001051827,0.00002591725,0.0001323485,0.000004516982,0.000007798856,0.00002328455,0.00001149638,0.9941031,0.001747668,0.003048578,0.0008801857,0.000004642635],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0283028,0.0001120217,0.9686952,0.00009155498,0.00002133175,0.00003782158,0.0000161863,0.0004836552,0.00223937],"genre_scores_gemma":[0.3808677,0.0001992268,0.615059,0.00005725515,0.00001908597,0.0001522339,0.00007653655,0.00007259657,0.003496435],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004727921,"threshold_uncertainty_score":0.009400845,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01351464334194153,"score_gpt":0.2279321280441724,"score_spread":0.2144174847022308,"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."}}