{"id":"W4394693322","doi":"10.1016/j.patcog.2024.110493","title":"Incremental convolutional transformer for baggage threat detection","year":2024,"lang":"en","type":"article","venue":"Pattern Recognition","topic":"Advanced Neural Network Applications","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Department of Education and Knowledge; Higher Education Commission, Pakistan; Khalifa University of Science, Technology and Research","keywords":"Computer science; Artificial intelligence; Clutter; Segmentation; Machine learning; Pattern recognition (psychology); Computer vision; Radar","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005581822,0.001156629,0.000803691,0.001689122,0.0005085294,0.0008913025,0.001473326,0.001001689,0.005427232],"category_scores_gemma":[0.001301978,0.0002979809,0.0007449751,0.001017485,0.0003905467,0.001611601,0.001522138,0.001432542,0.003540429],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000615329,"about_ca_system_score_gemma":0.001159862,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005788578,"about_ca_topic_score_gemma":0.01049172,"domain_scores_codex":[0.999536,0.00005299117,0.00001537403,0.0001044733,0.0001597027,0.0001314847],"domain_scores_gemma":[0.9995258,0.0001044272,0.0000353726,0.0001297552,0.0001480702,0.00005658064],"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":[0.0005514459,0.0003445511,0.005181585,0.0001218023,0.0001182118,0.0002655541,0.0000809651,0.02004307,0.03328419,0.006877932,0.0224473,0.9106834],"study_design_scores_gemma":[0.00001917563,0.0001851227,0.004316771,0.00003185807,0.00007605818,0.0005405631,0.00007159266,0.9439659,0.03061992,0.01149454,0.00864227,0.00003620038],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.118926,0.001433378,0.8567869,0.0005141632,0.0005014443,0.0002043821,0.001408557,0.009832669,0.01039252],"genre_scores_gemma":[0.8058043,0.0006422155,0.1727899,0.000394018,0.0001377921,0.00009202633,0.003941565,0.0003404606,0.01585769],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005788578,"threshold_uncertainty_score":0.01815593,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03851290604190102,"score_gpt":0.2811092132493741,"score_spread":0.2425963072074731,"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."}}