{"id":"W4286571870","doi":"10.1109/vlsitechnologyandcir46769.2022.9830315","title":"A 39,000 Subexposures/s CMOS Image Sensor with Dual-tap Coded-exposure Data-memory Pixel for Adaptive Single-shot Computational Imaging","year":2022,"lang":"en","type":"article","venue":"2022 IEEE Symposium on VLSI Technology and Circuits (VLSI Technology and Circuits)","topic":"Advanced Optical Sensing Technologies","field":"Physics and Astronomy","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Image sensor; Dynamic range; Computer science; Pixel; Artificial intelligence; Frame rate; Image resolution; NMOS logic; Computer vision; Wide dynamic range; CMOS; Electronic engineering; Transistor; Physics; Engineering","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0001648217,0.0002536284,0.0003540152,0.0001778821,0.0001560908,0.0003469945,0.001023328,0.000511713,0.00212174],"category_scores_gemma":[0.0003508707,0.0002575016,0.0001300434,0.0001752648,0.0001934076,0.0006582779,0.0004959998,0.0005199467,0.000620792],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003469184,"about_ca_system_score_gemma":0.0003897763,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004733243,"about_ca_topic_score_gemma":0.001286143,"domain_scores_codex":[0.9998265,0.000008724029,0.000008725011,0.0000374571,0.0001008281,0.0000178032],"domain_scores_gemma":[0.9998174,0.00003636027,0.00002762932,0.00002021844,0.00006921597,0.00002911613],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005788338,0.00003739164,0.0002483966,0.00005641174,0.000004608565,0.00007995109,0.00001925928,0.0002435039,0.9809201,0.000443468,0.0005438048,0.01734533],"study_design_scores_gemma":[0.00001660891,0.0002263581,0.001360279,0.000006806551,0.00001211016,0.0007056229,0.00001575142,0.01643518,0.9754816,0.0001257456,0.005596136,0.00001776741],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6192048,0.001857657,0.3641434,0.001019979,0.0003671818,0.0003044294,0.000848318,0.002862218,0.009392076],"genre_scores_gemma":[0.6790434,0.0004876404,0.3127469,0.0004198166,0.00005205646,0.0001377285,0.0003375126,0.00008612693,0.006688836],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00212174,"threshold_uncertainty_score":0.00709796,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01820265416858385,"score_gpt":0.2448565953345371,"score_spread":0.2266539411659532,"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."}}