{"id":"W7105614844","doi":"10.1109/lgrs.2025.3632353","title":"SFE-CapsNet: Spatial Feature Enhanced Capsule Networks for Remote Sensing Object Detection","year":2025,"lang":"","type":"article","venue":"IEEE Geoscience and Remote Sensing Letters","topic":"Advanced Neural Network Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Science Foundation of Fujian Province; National Natural Science Foundation of China; Natural Science Foundation of Xiamen City","keywords":"Fuse (electrical); Object detection; Convolutional neural network; Feature extraction; Feature (linguistics); Pyramid (geometry); Pattern recognition (psychology); Process (computing); Visualization","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","sts"],"consensus_categories":[],"category_scores_codex":[0.0007879976,0.0008145146,0.0007378123,0.0004887111,0.00293023,0.0008868555,0.0007593671,0.0004658937,7.734141e-7],"category_scores_gemma":[0.0001868989,0.0008470804,0.0003034098,0.00279112,0.001056707,0.0007139401,0.0003359314,0.001050762,0.00000722599],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003179503,"about_ca_system_score_gemma":0.0002183608,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001207339,"about_ca_topic_score_gemma":0.0008894434,"domain_scores_codex":[0.9940559,0.000262893,0.0007928124,0.002517401,0.0005799322,0.00179104],"domain_scores_gemma":[0.9968542,0.0004866609,0.0005773319,0.001400041,0.0003516023,0.0003301448],"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":[0.0000395376,0.000005977849,2.012064e-7,0.00004157319,0.00002159165,0.00001534963,0.0002587219,0.01052256,0.302789,0.000007321274,0.0004321217,0.685866],"study_design_scores_gemma":[0.0007405162,0.0001474922,0.0001543271,0.0006171095,0.00009907366,0.0001525956,0.00004559137,0.9042388,0.0896869,0.001042946,0.002298414,0.0007762849],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05847984,0.0004910382,0.9194158,0.01184313,0.007879948,0.001489584,0.000006895976,0.0002732631,0.0001205301],"genre_scores_gemma":[0.6538304,0.0004439546,0.3337239,0.009692446,0.001382133,3.962975e-7,0.000006807558,0.00005569363,0.0008642249],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8937162,"threshold_uncertainty_score":0.999398,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01023783711522969,"score_gpt":0.2479793826834936,"score_spread":0.2377415455682639,"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."}}