{"id":"W4403331717","doi":"10.23919/fusion59988.2024.10706502","title":"Leveraging Generative Deep Learning Models for Enhanced Change Detection in Heterogeneous Remote Sensing Data","year":2024,"lang":"en","type":"article","venue":"","topic":"Remote-Sensing Image Classification","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Canadian Space Agency","keywords":"Computer science; Generative grammar; Change detection; Generative model; Deep learning; Data modeling; Artificial intelligence; Remote sensing; Machine learning; Data science; Geography; Database","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008693284,0.0008203068,0.000698628,0.0009845579,0.0001813373,0.0006693623,0.001110654,0.0007551545,0.000771573],"category_scores_gemma":[0.001896013,0.0003583521,0.000770389,0.0007685554,0.0006190072,0.001139442,0.001165035,0.001252857,0.0003739785],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004596679,"about_ca_system_score_gemma":0.0003348138,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002079993,"about_ca_topic_score_gemma":0.003391132,"domain_scores_codex":[0.9996244,0.00008334692,0.00001515179,0.000126972,0.00009659075,0.00005348368],"domain_scores_gemma":[0.9992957,0.0003410179,0.0001091027,0.0001402058,0.00007906608,0.00003477473],"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":[0.0001902502,0.0001459385,0.005259912,0.0001273902,0.0001958657,0.0002988008,0.0001787176,0.6350297,0.02555444,0.007967312,0.002678008,0.3223737],"study_design_scores_gemma":[0.000001807231,0.00001073969,0.0003771678,0.000003234107,0.000007814549,0.00003720661,0.000009177176,0.9950363,0.002198044,0.001963206,0.0003508789,0.00000438668],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03431562,0.0003385761,0.9632106,0.0001879361,0.00003650256,0.00002963477,0.00009654544,0.000901529,0.0008830723],"genre_scores_gemma":[0.79543,0.0003212637,0.2003181,0.0003841353,0.0001069472,0.00005717476,0.0006453937,0.0001818775,0.00255506],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002079993,"threshold_uncertainty_score":0.004597545,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1077859149712707,"score_gpt":0.2840511133610563,"score_spread":0.1762651983897856,"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."}}