{"id":"W4414500333","doi":"10.1109/icscsa66339.2025.11170836","title":"A Comprehensive Review of Object Detection Using Deep Learning","year":2025,"lang":"en","type":"article","venue":"","topic":"Brain Tumor Detection and Classification","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Object detection; Deep learning; Object (grammar); Object-class detection; Process (computing); Camouflage; Viola–Jones object detection framework; Pattern recognition (psychology)","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009327831,0.00005884186,0.0001140515,0.00009522017,0.0001139542,0.00001032476,0.00006598699,0.00002567302,0.000106935],"category_scores_gemma":[0.0005348042,0.0000546112,0.00005368576,0.0006252066,0.00004467457,0.00006366881,0.00002241479,0.0001150069,0.00001475518],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003847284,"about_ca_system_score_gemma":0.0000207263,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001560753,"about_ca_topic_score_gemma":0.000002879693,"domain_scores_codex":[0.9992656,0.0001754478,0.0001919558,0.0001796587,0.0001064171,0.00008088481],"domain_scores_gemma":[0.9995549,0.0001358342,0.00009990162,0.0001221961,0.00007060623,0.00001659815],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000006862653,0.00001229378,0.00002911969,0.0008625434,0.000001777907,4.042774e-7,0.00001623061,0.00004595822,0.9507054,0.0006293692,0.00001077366,0.04767923],"study_design_scores_gemma":[0.0001384957,0.000030982,0.0012529,0.0007174361,0.00001537585,0.00001665255,0.0001128257,0.02374449,0.9572666,0.0001192401,0.01651594,0.00006902171],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6611514,0.009144235,0.2274624,0.001155065,0.001483933,0.001316,0.000001455162,0.0006883544,0.09759711],"genre_scores_gemma":[0.9957285,0.001779024,0.000154334,0.001676052,0.000009118026,0.000007100116,2.346471e-7,0.000004451584,0.0006411721],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3345771,"threshold_uncertainty_score":0.222698,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05289407494287027,"score_gpt":0.3188552236390994,"score_spread":0.2659611486962291,"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."}}