{"id":"W1502274547","doi":"","title":"FPGA based stereo vision system to show video of dense disparity map","year":2012,"lang":"en","type":"article","venue":"Society of Instrument and Control Engineers of Japan","topic":"Advanced Vision and Imaging","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Computer science; Computer vision; Artificial intelligence; Computer stereo vision; Field-programmable gate array; Video Graphics Array; Raster scan; Computer graphics (images); Matching (statistics); Stereopsis; Tone mapping; High dynamic range; Mathematics; Computer hardware; Dynamic range","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":[0.0001205892,0.0003629029,0.0002543263,0.0005794187,0.0001720388,0.0003530136,0.0005531004,0.0002461237,0.02292793],"category_scores_gemma":[0.0002778939,0.0001400681,0.0001241234,0.0003361217,0.00006902968,0.0002618186,0.0001996564,0.0002744727,0.002957553],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002685706,"about_ca_system_score_gemma":0.0002704232,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009344523,"about_ca_topic_score_gemma":0.001142534,"domain_scores_codex":[0.9998969,0.0000110062,0.000006009991,0.00001772733,0.0000457893,0.0000226044],"domain_scores_gemma":[0.9999017,0.0000170086,0.000008821368,0.00001421758,0.00004858504,0.000009689893],"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":[0.001064371,0.0003220713,0.003242805,0.0009776119,0.00008578188,0.001540432,0.0003593777,0.01369548,0.3864777,0.01985587,0.08314823,0.4892304],"study_design_scores_gemma":[0.0005962659,0.001575559,0.0119294,0.0001702568,0.0001584587,0.004629549,0.0001573722,0.2069132,0.5071945,0.004239215,0.262321,0.0001151397],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1446421,0.001015711,0.6869744,0.000462608,0.0009740706,0.0009804132,0.002784163,0.0376491,0.1245174],"genre_scores_gemma":[0.7644258,0.0005020141,0.1758442,0.0004564296,0.0001403404,0.0005331243,0.00190731,0.0005137167,0.05567712],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02292793,"threshold_uncertainty_score":0.07670158,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006589162796740412,"score_gpt":0.2229175159825638,"score_spread":0.2163283531858234,"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."}}