{"id":"W4403775011","doi":"10.3390/rs16213961","title":"Multi-Scale and Multi-Network Deep Feature Fusion for Discriminative Scene Classification of High-Resolution Remote Sensing Images","year":2024,"lang":"en","type":"article","venue":"Remote Sensing","topic":"Remote-Sensing Image Classification","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Wilfrid Laurier University","funders":"City University of Hong Kong","keywords":"Discriminative model; Remote sensing; Artificial intelligence; Computer science; High resolution; Pattern recognition (psychology); Scale (ratio); Feature (linguistics); Image fusion; Fusion; Computer vision; Geology; Cartography; Image (mathematics); Geography","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004921366,0.0003984729,0.0004466592,0.0002731346,0.000248868,0.0001724384,0.00008170986,0.0003199746,7.655486e-7],"category_scores_gemma":[0.0002344342,0.0004087957,0.000139846,0.0005053101,0.0001897626,0.0002948872,0.00005596816,0.0004025716,0.000007255232],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000329374,"about_ca_system_score_gemma":0.00003379126,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001325664,"about_ca_topic_score_gemma":0.0001651586,"domain_scores_codex":[0.9979442,0.000130544,0.0005096555,0.0006452711,0.000266016,0.0005042519],"domain_scores_gemma":[0.9986499,0.0003165751,0.0001537873,0.0004701135,0.0003093593,0.000100252],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002102396,0.000004877028,9.593736e-7,0.0003485969,0.00003574539,0.000007962957,0.0005042009,0.0068456,0.4608958,0.000006027891,0.0002171478,0.5311121],"study_design_scores_gemma":[0.0005092486,0.00002906396,0.002271315,0.001261175,0.0001538743,0.00009018191,0.0002748549,0.9499012,0.04432477,0.0003143138,0.0004854384,0.0003846152],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.07010452,0.002526758,0.9244128,0.0005343778,0.001028598,0.0006564394,0.00001988591,0.0006003909,0.0001162398],"genre_scores_gemma":[0.4618802,0.0002209829,0.5373615,0.00001175309,0.0002107916,1.935861e-8,0.00007757919,0.00009667116,0.0001405114],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9430556,"threshold_uncertainty_score":0.9998364,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02637440067172655,"score_gpt":0.2697393227894569,"score_spread":0.2433649221177303,"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."}}