{"id":"W4386325250","doi":"10.18280/ts.400433","title":"An Efficient Approach to Human Security Screening Image Recognition Through a Lightweight CNN Utilizing Yolov5s and GhostNet","year":2023,"lang":"en","type":"article","venue":"Traitement du signal","topic":"Face recognition and analysis","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Science Foundation of Anhui Province","keywords":"Computer science; Image (mathematics); Artificial intelligence; Pattern recognition (psychology); Computer vision","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.0002460331,0.0007393263,0.0005180323,0.0004919582,0.000215126,0.0005852629,0.001398664,0.0005177127,0.002705675],"category_scores_gemma":[0.0005600842,0.000291623,0.0004372883,0.0003447084,0.0002641212,0.0008185764,0.0009441071,0.0006490521,0.001201685],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006830452,"about_ca_system_score_gemma":0.0009572479,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01022544,"about_ca_topic_score_gemma":0.01806577,"domain_scores_codex":[0.9998592,0.00001096016,0.000005705912,0.00004715726,0.00004279549,0.00003418125],"domain_scores_gemma":[0.9998951,0.00001834865,0.00001426722,0.00002459488,0.00003616627,0.00001147494],"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":[0.000326548,0.0001901102,0.002742107,0.0001897733,0.000123276,0.0002713006,0.00008591901,0.1517467,0.07310464,0.008111633,0.01229386,0.7508141],"study_design_scores_gemma":[0.000006106215,0.00007278958,0.000739948,0.00001276002,0.00002340966,0.00008381659,0.00001828349,0.9822057,0.01252131,0.001500185,0.002806107,0.000009432208],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06588981,0.0009048646,0.9209924,0.0003948381,0.000240095,0.0001371548,0.0004827044,0.0052828,0.005675254],"genre_scores_gemma":[0.6566753,0.0009239253,0.3239899,0.0004819075,0.0001019413,0.0001753527,0.002032382,0.0001697413,0.01544953],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01022544,"threshold_uncertainty_score":0.02033186,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0471306087632789,"score_gpt":0.2850750921345707,"score_spread":0.2379444833712918,"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."}}