{"id":"W2367972984","doi":"","title":"Optimization Methods of Digital Image Process Algorithm on VLIW DSP","year":2008,"lang":"en","type":"article","venue":"Microcomputer applications","topic":"Image and Video Stabilization","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Very long instruction word; Computer science; Digital signal processing; Digital image processing; Image processing; Digital signal processor; Process (computing); Computer hardware; Algorithm; Embedded system; Image (mathematics); Artificial intelligence","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":[0.0004592446,0.0006757386,0.000484895,0.0004550384,0.0003464597,0.0004417519,0.0007185544,0.0003881605,0.002780092],"category_scores_gemma":[0.0009976745,0.0002872657,0.0004442103,0.000620448,0.0003187952,0.000555458,0.0003529265,0.0006928672,0.000585293],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005282298,"about_ca_system_score_gemma":0.000856988,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004579395,"about_ca_topic_score_gemma":0.003720257,"domain_scores_codex":[0.9996914,0.00006144017,0.00002115155,0.00004885501,0.0001537594,0.00002357021],"domain_scores_gemma":[0.9997346,0.00007785256,0.000021087,0.0000168646,0.000141216,0.000008331879],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001172716,0.00004888342,0.0007083818,0.0002362938,0.00006782429,0.00005769043,0.0001806021,0.5855917,0.02126162,0.02309137,0.003020475,0.3656179],"study_design_scores_gemma":[0.00001729803,0.00002068484,0.0001546978,0.000006364864,0.00000956464,0.00002006951,0.000009607726,0.9904447,0.005040742,0.001726353,0.002543123,0.000006723361],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003733174,0.000136342,0.9939963,0.00005001363,0.00001838543,0.00003432336,0.0000118412,0.0002201515,0.00179947],"genre_scores_gemma":[0.1512814,0.0006305184,0.8386358,0.00007117883,0.00005609656,0.000318903,0.0001390385,0.0002222605,0.008644741],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004579395,"threshold_uncertainty_score":0.009300292,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01585298907810469,"score_gpt":0.3110503352018706,"score_spread":0.295197346123766,"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."}}