{"id":"W787382797","doi":"10.1016/j.patcog.2015.05.028","title":"A novel Non-local means image denoising method based on grey theory","year":2015,"lang":"en","type":"article","venue":"Pattern Recognition","topic":"Image and Signal Denoising Methods","field":"Computer Science","cited_by":102,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Noise reduction; Computer science; Flexibility (engineering); Image (mathematics); Artificial intelligence; Noise (video); Set (abstract data type); Function (biology); Grey relational analysis; Pattern recognition (psychology); Mathematics; Algorithm; Statistics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0004420436,0.0005965633,0.001079297,0.0008675643,0.0003670032,0.0006492024,0.001110671,0.001136415,0.002021187],"category_scores_gemma":[0.0006499958,0.0003657568,0.001088061,0.0006986863,0.0005300503,0.00111938,0.0006659064,0.0009775637,0.0009035906],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003378142,"about_ca_system_score_gemma":0.0005584313,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001128228,"about_ca_topic_score_gemma":0.002024031,"domain_scores_codex":[0.9996389,0.00004172952,0.00001787852,0.0000799335,0.0002008656,0.00002058131],"domain_scores_gemma":[0.9997571,0.0000638736,0.00001909349,0.0000300762,0.0001113379,0.00001857169],"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":[0.0003104213,0.0001617515,0.0008871366,0.0006395682,0.0002440857,0.0002841585,0.0002370956,0.0545908,0.3082908,0.03182163,0.00547868,0.5970539],"study_design_scores_gemma":[0.00003643941,0.0001344768,0.0009676104,0.00002403042,0.0001054032,0.0006054331,0.00003127151,0.9234638,0.05773621,0.006903112,0.009926092,0.00006607796],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.004571002,0.0002898284,0.9938551,0.00006704612,0.00007547644,0.00001992933,0.00001687169,0.0001838623,0.0009209603],"genre_scores_gemma":[0.09836708,0.0008203515,0.8902494,0.0001415218,0.0001623084,0.0000910909,0.0001486772,0.0001680898,0.009851459],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002021187,"threshold_uncertainty_score":0.006761551,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05980202249865292,"score_gpt":0.3153552198604488,"score_spread":0.2555531973617959,"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."}}