{"id":"W2128714178","doi":"10.1155/asp.2005.1047","title":"An FPGA-Based People Detection System","year":2005,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Advanced Data Compression Techniques","field":"Computer Science","cited_by":48,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; JPEG; MicroBlaze; Field-programmable gate array; Discrete cosine transform; Frame rate; Computer hardware; Artificial intelligence; Process (computing); Background subtraction; Computer vision; Embedded system; Real-time computing; Data compression; Pixel; Image (mathematics)","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":[0.0001898709,0.0005248394,0.0005726855,0.0009781081,0.0003272544,0.0005050229,0.0008663883,0.0004837587,0.009021124],"category_scores_gemma":[0.0003756389,0.0002153527,0.0001862176,0.0003700014,0.0001448624,0.0004992863,0.0004325034,0.0002984116,0.003266831],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003329158,"about_ca_system_score_gemma":0.0003482318,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001552513,"about_ca_topic_score_gemma":0.001782483,"domain_scores_codex":[0.9996947,0.00002932016,0.00001827607,0.00007973346,0.0001340027,0.00004411862],"domain_scores_gemma":[0.9997959,0.00003910726,0.000019966,0.00002427993,0.00008690468,0.00003388462],"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":[0.001557366,0.0003801557,0.006912206,0.0006368767,0.0001422722,0.001255154,0.0002501641,0.01021534,0.1923434,0.003758784,0.03885768,0.7436906],"study_design_scores_gemma":[0.0007704541,0.00275639,0.02261291,0.0003353779,0.0004890411,0.006453168,0.0002729149,0.4012907,0.4031555,0.002842435,0.1587226,0.0002984324],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1955375,0.002160685,0.6979021,0.0006939957,0.001332808,0.0008437897,0.001306593,0.0515367,0.04868572],"genre_scores_gemma":[0.7895542,0.0007730045,0.1796878,0.0007416534,0.0002234874,0.0003759531,0.001055204,0.0002308832,0.02735787],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009021124,"threshold_uncertainty_score":0.03017873,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01148647843370195,"score_gpt":0.3024103474440572,"score_spread":0.2909238690103553,"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."}}