{"id":"W7130694051","doi":"10.1109/swc65939.2025.00084","title":"Comparison of small object detection approaches in unmanned aerial vehicle (UAV) images","year":2025,"lang":"","type":"article","venue":"","topic":"Advanced Neural Network Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Object detection; Benchmark (surveying); Convolutional neural network; Context (archaeology); Feature (linguistics); Deep learning; Aerial image; Generalization; Key (lock)","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":[0.0003279162,0.0003149814,0.0005939964,0.0003726869,0.000215582,0.0001168446,0.001063864,0.0001880476,0.00001631568],"category_scores_gemma":[0.0000775006,0.0003359382,0.0001359046,0.002831591,0.0002416437,0.0004092689,0.0006239453,0.0004157056,0.00002123646],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001448571,"about_ca_system_score_gemma":0.0001401521,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001577082,"about_ca_topic_score_gemma":0.0008578757,"domain_scores_codex":[0.9970924,0.0002323159,0.001019686,0.000898321,0.0002298706,0.0005274381],"domain_scores_gemma":[0.9981251,0.0003837178,0.0003434938,0.0009529612,0.0001118646,0.00008290864],"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":[0.0003107048,0.001548318,0.01361292,0.0002283122,0.00006993071,0.000002910286,0.001283938,0.0997475,0.06874835,0.03792377,0.0003198386,0.7762035],"study_design_scores_gemma":[0.0007747725,0.0001552783,0.01600331,0.0000672321,0.00002088491,0.000001120006,0.0001903267,0.6429572,0.3348643,0.004400298,0.000322798,0.0002425767],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1654103,0.0006843131,0.8258801,0.0009750435,0.0006447373,0.0009113179,0.000003286408,0.000129001,0.005361946],"genre_scores_gemma":[0.9699721,0.00005215184,0.02900296,0.0000823071,0.00009047303,0.0001115904,0.000002682503,0.0000138441,0.000671891],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8045619,"threshold_uncertainty_score":0.9999093,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06464606045802494,"score_gpt":0.3127073072439602,"score_spread":0.2480612467859352,"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."}}