{"id":"W2145984902","doi":"10.1109/tip.2011.2167344","title":"Image Registration Under Illumination Variations Using Region-Based Confidence Weighted $M$-Estimators","year":2011,"lang":"en","type":"article","venue":"IEEE Transactions on Image Processing","topic":"Advanced Image and Video Retrieval Techniques","field":"Computer Science","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Image registration; Estimator; Artificial intelligence; Computer vision; Computer science; Image processing; Confidence interval; Pattern recognition (psychology); Mathematics; Image (mathematics); Statistics","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":[0.002473629,0.0007926396,0.001159109,0.001049448,0.0003649298,0.00117833,0.002110202,0.001787614,0.001180793],"category_scores_gemma":[0.007888379,0.000640004,0.001531698,0.001201727,0.001180314,0.00192896,0.001819198,0.001759521,0.0009539706],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006048965,"about_ca_system_score_gemma":0.000859595,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001229224,"about_ca_topic_score_gemma":0.001322398,"domain_scores_codex":[0.9982639,0.000501454,0.00009379554,0.0004535916,0.0005855076,0.0001017625],"domain_scores_gemma":[0.9975801,0.0008550678,0.0005036468,0.0005958273,0.0004100572,0.00005529978],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003182415,0.0001024235,0.001650652,0.0002099153,0.0001955264,0.0001811553,0.0002161167,0.59574,0.06530716,0.02475978,0.001630306,0.3096888],"study_design_scores_gemma":[0.00000674844,0.00005712923,0.0003760872,0.000008659427,0.00001798867,0.0001000358,0.00001026677,0.9825974,0.01157803,0.003995614,0.001228502,0.00002357311],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002299231,0.00005947913,0.9973344,0.00002129898,0.000006297763,0.000009534448,0.000006776751,0.0001486471,0.0001143502],"genre_scores_gemma":[0.1644902,0.0002764394,0.8329224,0.000110007,0.00006261437,0.0001302419,0.0001317551,0.0002804034,0.001595901],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002473629,"threshold_uncertainty_score":0.01308191,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0487698456693913,"score_gpt":0.3019169394920037,"score_spread":0.2531470938226124,"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."}}