{"id":"W4410915038","doi":"10.1007/978-3-031-91979-4_22","title":"MCUBench: A Benchmark of Tiny Object Detectors on MCUs","year":2025,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Neural Network Applications","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Deep River Science Academy","funders":"","keywords":"Computer science; Benchmark (surveying); Detector; Object (grammar); Artificial intelligence; Computer vision; Computer graphics (images); Telecommunications; Cartography","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":[0.00130894,0.002101875,0.001140299,0.00207,0.0009837868,0.001425749,0.004431526,0.002088937,0.01318164],"category_scores_gemma":[0.006299912,0.0007675202,0.0007944949,0.002420147,0.0009112465,0.002571531,0.001780598,0.001232106,0.005475427],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001832058,"about_ca_system_score_gemma":0.002096501,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02010854,"about_ca_topic_score_gemma":0.02750204,"domain_scores_codex":[0.9982699,0.0002111069,0.00009948939,0.0003850985,0.000821774,0.0002126685],"domain_scores_gemma":[0.9979144,0.0006285309,0.0001109524,0.0004829223,0.0006746693,0.0001885987],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002733937,0.0005053717,0.005821041,0.002370378,0.0006961882,0.0005859553,0.0002302016,0.104371,0.0252582,0.01709806,0.4846078,0.3557218],"study_design_scores_gemma":[0.0005579498,0.0008202789,0.005927323,0.0002135407,0.000216512,0.000568183,0.0002232931,0.7548676,0.09841911,0.01597731,0.1220197,0.0001892416],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.3908533,0.01828885,0.1519786,0.003076996,0.003555153,0.001440686,0.04214261,0.2590653,0.1295985],"genre_scores_gemma":[0.6238714,0.002353152,0.2686138,0.001577388,0.0003155103,0.0007511654,0.06023658,0.009149262,0.03313183],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02010854,"threshold_uncertainty_score":0.04409701,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01376216611740025,"score_gpt":0.2538293027686813,"score_spread":0.2400671366512811,"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."}}