{"id":"W3111097319","doi":"10.18280/ts.370510","title":"Clustering-Based Band Selection Using Structural Similarity Index and Entropy for Hyperspectral Image Classification","year":2020,"lang":"en","type":"article","venue":"Traitement du signal","topic":"Remote-Sensing Image Classification","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Hyperspectral imaging; Pattern recognition (psychology); Artificial intelligence; Cluster analysis; Entropy (arrow of time); Classifier (UML); Computer science; Dimensionality reduction; Mathematics; Feature selection; Spectral bands; Remote sensing; Geography","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":[],"consensus_categories":[],"category_scores_codex":[0.00009472357,0.0001855826,0.0001614154,0.00006745094,0.0001301295,0.0001316979,0.00006768342,0.00007798024,0.00003805804],"category_scores_gemma":[0.00002717447,0.0002026852,0.00005412872,0.0001417363,0.00005246315,0.0002328486,0.000007103997,0.0001372372,0.000001701253],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001824167,"about_ca_system_score_gemma":0.00002767765,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000642388,"about_ca_topic_score_gemma":0.000009750123,"domain_scores_codex":[0.9990314,0.00003056313,0.0002594117,0.0002762472,0.0001643195,0.0002380611],"domain_scores_gemma":[0.9996244,0.0000420565,0.00006326564,0.00008103805,0.00008113246,0.000108125],"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":[0.0001119244,0.00001005446,0.0008059829,0.0001335309,0.00002862426,9.575643e-7,0.0002233703,0.06201348,0.9348515,0.0000447158,0.000139387,0.001636436],"study_design_scores_gemma":[0.001014873,0.00007698695,0.01595157,0.00001264646,0.00004350969,0.000005336748,0.00006416696,0.9360777,0.04638942,0.00005319689,0.0001156433,0.0001949387],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4501649,0.00001671455,0.5487663,0.0004222709,0.0000665762,0.0003365734,0.00001458186,0.0001806426,0.00003152724],"genre_scores_gemma":[0.9677549,0.000002233245,0.03177462,0.0001149022,0.0002585781,0.000008137253,0.00004565904,0.00003904532,0.000001954286],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8884621,"threshold_uncertainty_score":0.8265263,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03740003056246662,"score_gpt":0.2530017474917653,"score_spread":0.2156017169292987,"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."}}