{"id":"W2807987505","doi":"10.5539/nct.v3n1p26","title":"Comparison of De-Noising Algorithms Technique","year":2018,"lang":"en","type":"article","venue":"Network and Communication Technologies","topic":"Image and Signal Denoising Methods","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Median filter; Algorithm; Gaussian filter; Filter (signal processing); Peak signal-to-noise ratio; Artificial intelligence; Mathematics; Gaussian noise; Gaussian; Noise (video); Computer science; Mean squared error; Pattern recognition (psychology); Image quality; Computer vision; Image (mathematics); Image processing; Statistics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001184055,0.0006593035,0.0006877211,0.001585667,0.0003834649,0.001154471,0.0007634079,0.001011365,0.002626208],"category_scores_gemma":[0.003312599,0.0001948601,0.0007738884,0.001142638,0.0003551879,0.001112684,0.0003847088,0.000502005,0.0007443478],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003913002,"about_ca_system_score_gemma":0.000617108,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001531381,"about_ca_topic_score_gemma":0.001701943,"domain_scores_codex":[0.9988844,0.0000981393,0.0001224823,0.0002186786,0.0005854749,0.00009072273],"domain_scores_gemma":[0.9982619,0.0005568884,0.0001484389,0.0001801514,0.0008179233,0.00003475042],"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":[0.001088212,0.0002216977,0.003997532,0.0009835485,0.0001935025,0.0001719565,0.0002211179,0.03426404,0.1265941,0.004329801,0.002181956,0.8257526],"study_design_scores_gemma":[0.0001166538,0.001989472,0.0278005,0.0002416396,0.0004421746,0.002452737,0.0006405612,0.4760158,0.4394479,0.004715458,0.04594943,0.0001875144],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2033326,0.008610292,0.7676412,0.0004379006,0.0005361352,0.0002295224,0.0003280218,0.001659028,0.01722524],"genre_scores_gemma":[0.4525989,0.005657642,0.5288028,0.0001611001,0.0001187641,0.0001678295,0.0008546252,0.0002054529,0.01143295],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002626208,"threshold_uncertainty_score":0.008785546,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03944352934463508,"score_gpt":0.3485308323325245,"score_spread":0.3090873029878894,"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."}}