{"id":"W4415969745","doi":"10.1109/iecon58223.2025.11221647","title":"Depth-Homography Registration Framework and YOLOv8n-Coordinate Attention Forest Fire Detection for Visible-Infrared UAV Imagery","year":2025,"lang":"","type":"article","venue":"","topic":"Fire Detection and Safety Systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Fire detection; Multispectral image; RGB color model; Object detection; Calibration; Homography; Bounding overwatch; Image registration; Sensor fusion","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0004675769,0.001050922,0.001049585,0.0008717327,0.0003008331,0.000862651,0.001930174,0.0007960363,0.002534615],"category_scores_gemma":[0.001038695,0.0005780386,0.001371317,0.0007330826,0.0004503386,0.0007554952,0.001473873,0.001230507,0.001154815],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007115768,"about_ca_system_score_gemma":0.001164545,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01628956,"about_ca_topic_score_gemma":0.01747155,"domain_scores_codex":[0.9995685,0.00005511188,0.0000169969,0.0001664059,0.0001270189,0.00006594116],"domain_scores_gemma":[0.9997919,0.00003456756,0.00003530311,0.00005146403,0.00006533717,0.00002144491],"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":[0.0002807608,0.0001287067,0.002535525,0.0001633207,0.0001326162,0.000146931,0.0001729748,0.3418707,0.02444969,0.008188956,0.004188054,0.6177416],"study_design_scores_gemma":[0.000006386374,0.00004197145,0.0006980498,0.000009049951,0.00001137833,0.00005993624,0.00001533979,0.9928502,0.003581238,0.001028984,0.00168748,0.00001000578],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01049082,0.0002440006,0.9863051,0.00006390573,0.00003548602,0.00005143699,0.0001413337,0.001600577,0.001067368],"genre_scores_gemma":[0.4072258,0.0006696724,0.5822403,0.0002379546,0.0001330341,0.0002408685,0.001787168,0.0004737644,0.006991309],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01628956,"threshold_uncertainty_score":0.03238952,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007545626718371791,"score_gpt":0.2357896961755845,"score_spread":0.2282440694572127,"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."}}