{"id":"W2000281317","doi":"10.1109/igarss.2011.6050030","title":"Registration of multi-frequency SAR imagery using phase correlation methods","year":2011,"lang":"en","type":"article","venue":"","topic":"Synthetic Aperture Radar (SAR) Applications and Techniques","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Synthetic aperture radar; Remote sensing; Interferometric synthetic aperture radar; Constellation; Radar imaging; Inverse synthetic aperture radar; Artificial intelligence; Computer vision; Image registration; Radar; Geology; Image (mathematics); Telecommunications","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":[0.000664209,0.0006213851,0.0004049168,0.001599506,0.0003497314,0.001006516,0.0005697246,0.0006173115,0.002541561],"category_scores_gemma":[0.002454762,0.0004048593,0.0005651482,0.002065953,0.0004715783,0.001252726,0.0008251144,0.0008251966,0.001501498],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003317258,"about_ca_system_score_gemma":0.0008446266,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009469228,"about_ca_topic_score_gemma":0.00180296,"domain_scores_codex":[0.999295,0.0001646264,0.0000395569,0.0001555778,0.0002947611,0.00005051811],"domain_scores_gemma":[0.9991136,0.0002352024,0.0001650897,0.0002459775,0.000215875,0.00002427644],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002088083,0.0001935935,0.001577532,0.0001904749,0.00008944124,0.0002024963,0.0002787527,0.09901189,0.1430042,0.01941218,0.003168682,0.7326619],"study_design_scores_gemma":[0.00004006269,0.0001384042,0.003138186,0.0000282898,0.0000438748,0.0004858752,0.0001078078,0.878081,0.08966084,0.009857283,0.01834937,0.00006908112],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01132613,0.00008168576,0.9864224,0.00006318324,0.00003670647,0.00004558154,0.00006189472,0.0005351811,0.001427309],"genre_scores_gemma":[0.1030365,0.0002471914,0.8934225,0.00006179886,0.00005853689,0.0001066135,0.0003822833,0.0002232107,0.002461378],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002541561,"threshold_uncertainty_score":0.008502424,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06681276996587972,"score_gpt":0.3425814238418518,"score_spread":0.2757686538759721,"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."}}