{"id":"W4386897337","doi":"10.36713/epra14418","title":"ADVANCEMENTS IN OBJECT DETECTION AND TRACKING ALGORITHMS: AN OVERVIEW OF RECENT PROGRESS","year":2023,"lang":"en","type":"article","venue":"EPRA International Journal of Research & Development (IJRD)","topic":"Advanced Neural Network Applications","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Computer science; Artificial intelligence; Object detection; Video tracking; Convolutional neural network; Deep learning; Robotics; Computer vision; Machine learning; Object (grammar); Robot; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002840328,0.001235419,0.0007739139,0.003687322,0.0004425596,0.00210212,0.001383119,0.001591313,0.002881978],"category_scores_gemma":[0.004724219,0.0008317188,0.0007562966,0.004650713,0.0008495224,0.004700518,0.001488054,0.002553041,0.002108055],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001345687,"about_ca_system_score_gemma":0.001450466,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003257128,"about_ca_topic_score_gemma":0.001936947,"domain_scores_codex":[0.9986485,0.0001995574,0.0001664181,0.0003378013,0.0005528156,0.0000948666],"domain_scores_gemma":[0.9969932,0.001354737,0.0002130774,0.0001418457,0.001162429,0.0001346566],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001032572,0.0001002577,0.001365452,0.002637736,0.00006606768,0.00006611414,0.0001138504,0.004470922,0.002375138,0.01154668,0.0132727,0.9638819],"study_design_scores_gemma":[0.00002245053,0.0004383994,0.003750433,0.003460606,0.0002894701,0.001029962,0.0003057904,0.04306233,0.01076824,0.02616174,0.9105492,0.0001613678],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.004457694,0.8933722,0.08709051,0.003242211,0.001057682,0.00005818374,0.0001976374,0.0005858768,0.00993805],"genre_scores_gemma":[0.04253905,0.8783333,0.06932937,0.001396037,0.002042338,0.0000847184,0.0008325318,0.000189186,0.005253507],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.003687322,"threshold_uncertainty_score":0.01502126,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1998817750059806,"score_gpt":0.4750446525250136,"score_spread":0.275162877519033,"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."}}