{"id":"W2389549257","doi":"","title":"Image Restoration Algorithm Base on BP Neural Network Optimized by Genetic and LM Algorithm","year":2010,"lang":"en","type":"article","venue":"Microcomputer applications","topic":"Optical Systems and Laser Technology","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Algorithm; Computer science; Genetic algorithm; Population-based incremental learning; Artificial neural network; Convergence (economics); Image (mathematics); Cultural algorithm; Value (mathematics); Base (topology); Artificial intelligence; Mathematics; Machine learning","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":[0.0004011327,0.000504724,0.00075246,0.0006527813,0.0004821346,0.000606351,0.0009079575,0.0008618552,0.002275748],"category_scores_gemma":[0.0007456402,0.0002416405,0.0004248739,0.0005675509,0.0003291508,0.0006974539,0.0003793263,0.0008235678,0.0007146094],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005351374,"about_ca_system_score_gemma":0.0008725767,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00538854,"about_ca_topic_score_gemma":0.003756536,"domain_scores_codex":[0.9997237,0.00003599001,0.00001354745,0.00005586344,0.0001424865,0.00002828501],"domain_scores_gemma":[0.9998397,0.00003342412,0.00001880265,0.00001134902,0.00008820734,0.000008509071],"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":[0.0001785536,0.0001120348,0.0007778691,0.0002547572,0.00008008039,0.0001553132,0.000112727,0.3911506,0.02927739,0.01200133,0.005761004,0.5601385],"study_design_scores_gemma":[0.00002835508,0.00004622613,0.0003105934,0.00001733033,0.00002249331,0.00009931008,0.00001325529,0.985914,0.007163762,0.002554692,0.003812527,0.00001740321],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.006482161,0.0003142659,0.9874992,0.0001332167,0.00007034021,0.00005236411,0.00002168304,0.001360453,0.004066348],"genre_scores_gemma":[0.2781185,0.0008056074,0.7017342,0.0001789761,0.0001002099,0.0003763597,0.0001653413,0.0002201665,0.01830047],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00538854,"threshold_uncertainty_score":0.01071435,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003081873257843279,"score_gpt":0.192437205091387,"score_spread":0.1893553318335437,"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."}}