{"id":"W4200589011","doi":"10.3390/drones5040149","title":"Convolutional Neural Networks for Classification of Drones Using Radars","year":2021,"lang":"en","type":"article","venue":"Drones","topic":"Advanced SAR Imaging Techniques","field":"Engineering","cited_by":36,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University; Canada Research Chairs; University of Waterloo; University of Toronto; Defence Research and Development Canada","funders":"","keywords":"Spectrogram; Radar; Short-time Fourier transform; Computer science; Convolutional neural network; Drone; Artificial intelligence; Pulse repetition frequency; Noise (video); Pattern recognition (psychology); Time–frequency analysis; Autoregressive model; Artificial neural network; Speech recognition; Fourier transform; Telecommunications; Mathematics; Fourier analysis; Statistics","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":[0.0005321958,0.0006677894,0.000352293,0.0007098399,0.0002007534,0.0004484943,0.0005129502,0.0006352894,0.00124826],"category_scores_gemma":[0.001519709,0.0002359119,0.0003822994,0.0005190638,0.0002227797,0.0005149661,0.0004123564,0.0006878001,0.0004194203],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006664568,"about_ca_system_score_gemma":0.0003461792,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01262369,"about_ca_topic_score_gemma":0.01126281,"domain_scores_codex":[0.9998259,0.00003015806,0.00001414169,0.0000487542,0.00004321385,0.00003781128],"domain_scores_gemma":[0.9995827,0.0001951169,0.00005865012,0.00004020478,0.0001047125,0.00001855373],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003189292,0.0001540253,0.0114869,0.00009948882,0.000133701,0.0001861614,0.00008048226,0.6982959,0.01907946,0.001538198,0.002464368,0.2661625],"study_design_scores_gemma":[0.000002129196,0.00001955951,0.001790953,0.0000064381,0.000006020913,0.00001481529,0.00001190716,0.9954059,0.002127099,0.000369273,0.0002406318,0.00000516913],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7330821,0.002327427,0.2554365,0.0007518774,0.000246155,0.00008667127,0.001005253,0.001835075,0.005228956],"genre_scores_gemma":[0.9687207,0.0003713385,0.02715944,0.00006172331,0.00003838204,0.00002489413,0.0008582663,0.00002226963,0.002743179],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01262369,"threshold_uncertainty_score":0.02510041,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03233409572817,"score_gpt":0.2809832241831535,"score_spread":0.2486491284549835,"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."}}