{"id":"W2134736836","doi":"10.1109/ccece.2009.5090127","title":"PCA-whitening CSS shape descriptor for affine invariant image retrieval","year":2009,"lang":"en","type":"article","venue":"","topic":"Image Retrieval and Classification Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Affine transformation; Silhouette; Artificial intelligence; Mathematics; Pattern recognition (psychology); Invariant (physics); Principal component analysis; Image retrieval; Computer vision; Affine hull; Active shape model; Curvature; Affine shape adaptation; Shape analysis (program analysis); Computer science; Image (mathematics); Affine combination; Geometry; Affine space","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":[0.0005700117,0.0005945369,0.0008099422,0.002243476,0.000338759,0.0008530575,0.0008609565,0.0005341521,0.003550597],"category_scores_gemma":[0.001888958,0.0001982016,0.0007555104,0.00289493,0.0005315912,0.001473133,0.0005536542,0.0006192547,0.002518606],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006719182,"about_ca_system_score_gemma":0.0007874303,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002367931,"about_ca_topic_score_gemma":0.002143591,"domain_scores_codex":[0.9991774,0.00009212474,0.00005021712,0.0001298649,0.0004964477,0.00005388872],"domain_scores_gemma":[0.9991559,0.0001242944,0.00008343084,0.0002082803,0.0003883232,0.00003987647],"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":[0.0002416447,0.00009751807,0.001688921,0.000263107,0.00009910772,0.0001806707,0.00006182403,0.02229626,0.1302163,0.02373494,0.01213417,0.8089856],"study_design_scores_gemma":[0.00004628132,0.0004267191,0.008434065,0.00004247115,0.0001225259,0.001665702,0.00009358692,0.8022019,0.1268444,0.01236079,0.04756311,0.0001983737],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01816283,0.001357855,0.9749261,0.0001236401,0.0001668278,0.0001186415,0.0003500794,0.002189296,0.002604695],"genre_scores_gemma":[0.380488,0.002288528,0.6030112,0.0003057252,0.0003828737,0.0003603086,0.003485696,0.0004327804,0.009244913],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003550597,"threshold_uncertainty_score":0.01187789,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02729128991233723,"score_gpt":0.2699940512037933,"score_spread":0.242702761291456,"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."}}