{"id":"W4377832628","doi":"10.18280/ts.400228","title":"Pixel Optimization Using Iterative Pixel Compression Algorithm for Complementary Metal Oxide Semiconductor Image Sensors","year":2023,"lang":"en","type":"article","venue":"Traitement du signal","topic":"CCD and CMOS Imaging Sensors","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Prince Sattam bin Abdulaziz University","keywords":"Pixel; Computer science; Algorithm; Optimization algorithm; Semiconductor; Materials science; Computer vision; Artificial intelligence; Mathematics; Optoelectronics; Mathematical optimization","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":[0.0003155482,0.0004817831,0.0004085826,0.0006145147,0.0002895545,0.0004976255,0.0006407516,0.0005414836,0.001803101],"category_scores_gemma":[0.0007599927,0.0002031845,0.0004286205,0.000634721,0.000294514,0.0005089042,0.0003191074,0.0005075231,0.0004433345],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004579299,"about_ca_system_score_gemma":0.0007004454,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001993916,"about_ca_topic_score_gemma":0.002242742,"domain_scores_codex":[0.9996339,0.00003468487,0.00001778497,0.00005689937,0.0002316563,0.00002513464],"domain_scores_gemma":[0.9997491,0.00006390313,0.00003116365,0.00002605671,0.000121764,0.000008016765],"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":[0.0001857779,0.0001214121,0.001466981,0.0001823811,0.00008924252,0.0001736612,0.0002272388,0.1069638,0.1527637,0.01093212,0.002883242,0.7240105],"study_design_scores_gemma":[0.0000135558,0.0001911859,0.0009133087,0.00001600491,0.00002275135,0.0003232353,0.00002872613,0.9049332,0.08639114,0.001809312,0.005334522,0.00002303018],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02456733,0.0004015206,0.9715856,0.00008211297,0.0000501326,0.00007112163,0.00002393683,0.0006473453,0.002570798],"genre_scores_gemma":[0.1622833,0.0002998467,0.8335402,0.00008177859,0.00002769162,0.0001091777,0.0001132744,0.00007537656,0.003469315],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001993916,"threshold_uncertainty_score":0.00603199,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02986702626244448,"score_gpt":0.2671789512578486,"score_spread":0.2373119249954041,"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."}}