{"id":"W4402260472","doi":"10.1109/igarss53475.2024.10640940","title":"SpACNN-LDVAE: Spatial Attention Convolutional Latent Dirichlet Variational Autoencoder for Hyperspectral Pixel Unmixing","year":2024,"lang":"en","type":"article","venue":"","topic":"Remote-Sensing Image Classification","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Autoencoder; Hyperspectral imaging; Computer science; Pixel; Latent Dirichlet allocation; Artificial intelligence; Pattern recognition (psychology); Remote sensing; Deep learning; Geography; Topic model","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":[0.00100795,0.0008819826,0.0008388614,0.0004047804,0.000317688,0.0005655964,0.001442705,0.0009198888,0.001229632],"category_scores_gemma":[0.001749989,0.0005088712,0.0009345631,0.000481824,0.0005675304,0.001168239,0.001147493,0.001927889,0.0005046387],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009262413,"about_ca_system_score_gemma":0.001005455,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01234767,"about_ca_topic_score_gemma":0.02575932,"domain_scores_codex":[0.9996507,0.00009858348,0.00001565952,0.0001221155,0.00007275269,0.00004012746],"domain_scores_gemma":[0.9996222,0.0001694884,0.0000310526,0.00006376688,0.00009233036,0.00002108061],"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":[0.0001715313,0.0001685267,0.00204706,0.000124291,0.0002290487,0.0001028936,0.0001259554,0.7479611,0.01523481,0.01026275,0.006321703,0.2172504],"study_design_scores_gemma":[0.000002726014,0.000005189629,0.0001198122,0.000003279845,0.00000434707,0.000008994273,0.000003769513,0.9964014,0.001366914,0.001672299,0.0004072966,0.000003940997],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02621679,0.0006109989,0.9695948,0.0002638405,0.00008011993,0.00004130318,0.0003594116,0.001571586,0.001261101],"genre_scores_gemma":[0.5591125,0.0005963706,0.4259978,0.000510103,0.0001141889,0.0001607483,0.003030876,0.0004574547,0.01001996],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01234767,"threshold_uncertainty_score":0.02455157,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01687469234292295,"score_gpt":0.2385680418676597,"score_spread":0.2216933495247367,"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."}}