{"id":"W2982525009","doi":"10.1109/mwscas.2019.8885009","title":"Design of a 2D Median Filter with a High Throughput FPGA Implementation","year":2019,"lang":"en","type":"article","venue":"","topic":"Image and Signal Denoising Methods","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Field-programmable gate array; Median filter; Computer science; Throughput; Computer hardware; Filter (signal processing); Impulse noise; Histogram; Latency (audio); Finite impulse response; Embedded system; Real-time computing; Artificial intelligence; Computer vision; Algorithm; Image processing; 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":[0.0002095302,0.0004227728,0.0004049906,0.0006243393,0.0003160386,0.0007533686,0.0007718119,0.0005847594,0.004813653],"category_scores_gemma":[0.0003803839,0.000372193,0.0003358333,0.0004158241,0.0001478902,0.0005441313,0.0002560067,0.0002767826,0.001586401],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004989949,"about_ca_system_score_gemma":0.0005268586,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00122984,"about_ca_topic_score_gemma":0.001741837,"domain_scores_codex":[0.9997662,0.00001709119,0.00001454697,0.00005659349,0.0001109798,0.00003461979],"domain_scores_gemma":[0.9998597,0.00003491295,0.00001865104,0.00002102949,0.00005577074,0.000009970795],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006300039,0.00009807191,0.001837207,0.0003149838,0.0001465958,0.0005212759,0.0001551973,0.04242064,0.4125974,0.008733977,0.006108013,0.5264367],"study_design_scores_gemma":[0.0001634897,0.0008655504,0.003695807,0.00004706024,0.0001028214,0.001411514,0.00007650179,0.6072661,0.3390817,0.002387184,0.04481704,0.00008514067],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01379559,0.0001551321,0.9814874,0.00008071939,0.00006775637,0.00008375065,0.00009514932,0.002094656,0.002139934],"genre_scores_gemma":[0.1981774,0.0001805904,0.7962393,0.0001354479,0.00006282111,0.0001734187,0.0002549635,0.00009970916,0.004676498],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004813653,"threshold_uncertainty_score":0.01610321,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03212854747015955,"score_gpt":0.3043484835823133,"score_spread":0.2722199361121537,"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."}}