{"id":"W2114914430","doi":"10.1109/ccece.2004.1349633","title":"Evaluation of image corner detectors for hardware implementation","year":2004,"lang":"en","type":"article","venue":"","topic":"Advanced Image and Video Retrieval Techniques","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Field-programmable gate array; Stability (learning theory); Detector; Algorithm; Computer science; Software; Computational complexity theory; Simple (philosophy); Computer engineering; Computer hardware; Machine learning","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006717088,0.00006089327,0.00007459548,0.00006078983,0.00003939271,0.00002675333,0.0002016136,0.00002018274,0.00003277733],"category_scores_gemma":[0.0001039283,0.00005236326,0.00004731937,0.0001755618,0.00001652391,0.0006684808,0.00004357665,0.00002214586,0.000003383322],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000852363,"about_ca_system_score_gemma":0.0001044853,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002620526,"about_ca_topic_score_gemma":0.00001380132,"domain_scores_codex":[0.9991928,0.00002359501,0.0001682951,0.0001637864,0.0003421629,0.0001093612],"domain_scores_gemma":[0.9990106,0.0000270596,0.00008257011,0.0002094669,0.000647291,0.00002299845],"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":[0.000006477592,0.00003661468,0.00006265911,0.00001660222,0.00001422719,3.256575e-7,0.000242903,0.00007133335,0.1058944,0.02314861,0.0003788563,0.870127],"study_design_scores_gemma":[0.0006667888,0.00015036,0.000619787,0.000006116456,0.00001631428,0.000001020706,0.00004530463,0.002086343,0.9162588,0.07978699,0.0002938399,0.00006831143],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008921004,0.0000374524,0.9897627,0.0001134745,0.0000513909,0.0005162099,0.000004316432,0.0001208081,0.000472698],"genre_scores_gemma":[0.6201805,0.000003934127,0.3796699,0.00005716144,0.00001277072,0.0000525265,0.000004501868,0.000004022448,0.00001464123],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8700587,"threshold_uncertainty_score":0.2135312,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0516962702497527,"score_gpt":0.3953693459465764,"score_spread":0.3436730756968236,"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."}}