{"id":"W4402916307","doi":"10.1109/cvprw63382.2024.00474","title":"Drone-HAT: Hybrid Attention Transformer for Complex Action Recognition in Drone Surveillance Videos","year":2024,"lang":"en","type":"article","venue":"","topic":"Anomaly Detection Techniques and Applications","field":"Computer Science","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo; University of Ottawa","funders":"","keywords":"Drone; Transformer; Computer science; Action recognition; Artificial intelligence; Action (physics); Computer vision; Engineering; Electrical engineering; Physics; Voltage","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":[0.0003541389,0.000830314,0.0006010151,0.001202186,0.0002041624,0.0004984548,0.0008506686,0.0004291436,0.002840976],"category_scores_gemma":[0.000681883,0.0002094237,0.0005301342,0.0005050501,0.0002329434,0.0007540147,0.0006682284,0.0005923203,0.0009360585],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00051767,"about_ca_system_score_gemma":0.0004842782,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01136639,"about_ca_topic_score_gemma":0.0189287,"domain_scores_codex":[0.9997556,0.00002388769,0.000009308667,0.0001003841,0.00006159642,0.00004922698],"domain_scores_gemma":[0.9998168,0.00005096327,0.00001792061,0.00002738664,0.00005846112,0.0000285169],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003908511,0.0002390886,0.002232779,0.0001375805,0.0001144797,0.0002022446,0.00008241449,0.01793277,0.1031224,0.001410451,0.009398209,0.8647367],"study_design_scores_gemma":[0.00003521655,0.0001997733,0.00468514,0.00001268293,0.00005528782,0.0002635409,0.00006239768,0.9361966,0.05296319,0.001523618,0.00397852,0.00002408335],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1120893,0.00108857,0.8680584,0.0001647265,0.000192932,0.0003244066,0.000871496,0.01280529,0.00440485],"genre_scores_gemma":[0.7213203,0.0005188736,0.2680748,0.0003198674,0.00009129749,0.0001448779,0.002463741,0.0002734481,0.006792701],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01136639,"threshold_uncertainty_score":0.02260047,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06099052872930029,"score_gpt":0.3158575865927183,"score_spread":0.2548670578634181,"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."}}