{"id":"W1716119910","doi":"10.1109/icdsp.1997.628028","title":"Directional detail histogram for content based image retrieval","year":2002,"lang":"en","type":"article","venue":"","topic":"Image Retrieval and Classification Techniques","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Histogram; Computer science; Search engine indexing; Image histogram; Image texture; Image retrieval; Artificial intelligence; Computer vision; Content-based image retrieval; Image (mathematics); Histogram matching; Randomness; Pattern recognition (psychology); Information retrieval; Image processing; Mathematics","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":[0.0002022235,0.00009919417,0.000106568,0.00007760512,0.0001338493,0.0001264211,0.0003919789,0.00004979084,0.0002871596],"category_scores_gemma":[0.0001140922,0.000083158,0.0001238001,0.0002763169,0.00005682757,0.000302133,0.00003566123,0.00006334114,0.00008260053],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007492256,"about_ca_system_score_gemma":0.00002223682,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006858661,"about_ca_topic_score_gemma":9.771965e-7,"domain_scores_codex":[0.9990771,0.00002493569,0.0001953016,0.0002851622,0.0002260794,0.0001913723],"domain_scores_gemma":[0.9991662,0.0001093197,0.0000649474,0.0003152093,0.0002696549,0.00007467739],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00008876812,0.001001591,0.0003020854,0.00007156372,0.00004462311,0.000009537935,0.000130672,5.540714e-7,0.5465975,0.176631,0.05092717,0.224195],"study_design_scores_gemma":[0.0004664144,0.000165943,0.0003656238,0.000005735398,0.000005925476,0.000006691978,0.000007466216,0.08577161,0.7773304,0.0009844911,0.1346837,0.0002060593],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00009328273,0.00009454724,0.9882849,0.003793791,0.0001804904,0.0002607769,0.000003987993,0.0007064537,0.006581724],"genre_scores_gemma":[0.06377228,0.00001785148,0.9105924,0.001404067,0.0000822181,0.00007248293,0.000006515045,0.00001301216,0.02403918],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.2307329,"threshold_uncertainty_score":0.3391085,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08432482724436725,"score_gpt":0.2578779528205696,"score_spread":0.1735531255762024,"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."}}