{"id":"W4386919833","doi":"10.1109/sas58821.2023.10254115","title":"Spectral-Spatial-Frequency Transformer Network for Hyperspectral Image Classification","year":2023,"lang":"en","type":"article","venue":"","topic":"Remote-Sensing Image Classification","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Hyperspectral imaging; Computer science; Transformer; Artificial intelligence; Pattern recognition (psychology); Remote sensing; Geology; Engineering; Electrical engineering; Voltage","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002297525,0.0001990123,0.0001811423,0.0001250821,0.0001097077,0.00008246712,0.0001483173,0.0001141775,0.00007573565],"category_scores_gemma":[0.00004460409,0.0002020799,0.0001254322,0.0005327598,0.00005122779,0.0002531929,0.000003342506,0.0001376062,0.0004913265],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001526588,"about_ca_system_score_gemma":0.00002559582,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002582246,"about_ca_topic_score_gemma":0.00006700557,"domain_scores_codex":[0.9986948,0.00001745704,0.0003181158,0.0002828471,0.0001607016,0.000526123],"domain_scores_gemma":[0.999363,0.00009542182,0.0000310837,0.0003473628,0.00007789316,0.00008522071],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000132984,0.00001768928,0.0001537635,0.0000931648,0.0000524972,0.000004137487,0.0002567818,0.00575285,0.9116673,0.008506478,0.04754399,0.02593809],"study_design_scores_gemma":[0.0006205688,0.00006069989,0.03848109,0.00002890873,0.00005178518,0.0000105305,0.0001976359,0.8877295,0.05661033,0.008804921,0.006862089,0.0005419755],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05792199,0.0000874481,0.8661084,0.002488507,0.001225782,0.001078231,0.00002842489,0.004008087,0.06705318],"genre_scores_gemma":[0.902871,0.0001903099,0.09400753,0.00006024221,0.0008049543,0.00006778255,0.0002624818,0.0001380424,0.001597677],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8819766,"threshold_uncertainty_score":0.8240578,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02703942678233791,"score_gpt":0.2530126333482953,"score_spread":0.2259732065659574,"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."}}