{"id":"W2141794039","doi":"10.1109/pacrim.1997.620322","title":"Neural network stereo image segmentation for directed coordinate measuring machine part programming","year":2002,"lang":"en","type":"article","venue":"","topic":"Optical measurement and interference techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Artificial intelligence; Computer vision; Computer science; Digitization; Robustness (evolution); Stereo camera; Segmentation; Computer stereo vision","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":[0.0002963281,0.0004428259,0.000412766,0.000501357,0.0002718857,0.0003291527,0.0009298224,0.0006383877,0.003898446],"category_scores_gemma":[0.0007924485,0.0002970256,0.0003448948,0.0006133172,0.0002938905,0.0004173766,0.0003690566,0.0004866048,0.0006510076],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001121684,"about_ca_system_score_gemma":0.0007605271,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007680176,"about_ca_topic_score_gemma":0.01031546,"domain_scores_codex":[0.9998222,0.00002965763,0.000008237581,0.00005635547,0.00006214907,0.00002144607],"domain_scores_gemma":[0.9997545,0.00008230023,0.00003773996,0.00003796543,0.00007586062,0.00001154205],"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":[0.0001418954,0.00007793205,0.0005017628,0.00008665556,0.0000296634,0.0000812969,0.00006230849,0.3933946,0.03727183,0.01006159,0.003215384,0.555075],"study_design_scores_gemma":[0.000003993995,0.00001383642,0.0001566839,0.00000246685,0.000002700545,0.00001103159,0.000002988381,0.9939309,0.003428404,0.001736606,0.0007072618,0.000003047554],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.009807087,0.00008302977,0.9866833,0.00006302661,0.00001812328,0.00004768595,0.00007144309,0.001701253,0.001525069],"genre_scores_gemma":[0.2734821,0.000121166,0.7206151,0.0001304447,0.00003403032,0.0002970922,0.0003522711,0.0001520463,0.004815724],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.007680176,"threshold_uncertainty_score":0.01527095,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07044881784740652,"score_gpt":0.2693018596956396,"score_spread":0.1988530418482331,"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."}}