{"id":"W4406267132","doi":"10.1109/vtc2024-fall63153.2024.10757938","title":"Integrating Visual Geometry and Mask Region CNN for Enhanced UAV Detection and Identification","year":2024,"lang":"en","type":"article","venue":"","topic":"Industrial Vision Systems and Defect Detection","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Identification (biology); Computer vision; Computer science; Artificial intelligence; Computer graphics (images); Computational geometry; Geometry; Mathematics","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":[0.0002667514,0.0007133557,0.0003297139,0.0004771481,0.0001167862,0.0003280249,0.0006968264,0.0003916062,0.0007151728],"category_scores_gemma":[0.0007954392,0.0002229703,0.000286007,0.0003344064,0.0002173189,0.000667304,0.0005973917,0.0003496297,0.0003051091],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005280818,"about_ca_system_score_gemma":0.0004686143,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007836464,"about_ca_topic_score_gemma":0.01257896,"domain_scores_codex":[0.9998473,0.00001489939,0.000005506826,0.00004650377,0.00005435758,0.00003140023],"domain_scores_gemma":[0.9998085,0.00003939967,0.00003377278,0.00003891585,0.00006643336,0.00001310785],"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":[0.000244052,0.0001418453,0.006697558,0.0001296173,0.0001170468,0.0002751984,0.00008462447,0.3633704,0.1229519,0.003541235,0.003676459,0.49877],"study_design_scores_gemma":[0.000002218954,0.00004360356,0.001301083,0.000004925285,0.00001524708,0.00007752453,0.000008479928,0.9827049,0.01447639,0.0005517586,0.0008078461,0.000006026223],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2328993,0.0008324806,0.7576868,0.0002656512,0.0001395168,0.000087026,0.0003892038,0.002425584,0.005274414],"genre_scores_gemma":[0.8199096,0.0003284533,0.175422,0.0001493769,0.00003502817,0.00003346149,0.0005846007,0.00006979363,0.003467672],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007836464,"threshold_uncertainty_score":0.01558167,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01444571154683882,"score_gpt":0.2594141911228681,"score_spread":0.2449684795760292,"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."}}