{"id":"W2384804245","doi":"","title":"A Method of Image Retrieval Based on Edge and Color Feature","year":2008,"lang":"en","type":"article","venue":"Microcomputer applications","topic":"Image Retrieval and Classification Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Artificial intelligence; Computer vision; Image gradient; Feature (linguistics); HSL and HSV; Color image; Pattern recognition (psychology); Edge detection; Enhanced Data Rates for GSM Evolution; Image retrieval; Color histogram; Feature detection (computer vision); Color quantization; Color space; Precision and recall; Image segmentation; Image texture; Image (mathematics); Image processing","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005821185,0.0005905944,0.001145448,0.002743549,0.0006987436,0.00137547,0.00140439,0.001057477,0.00403484],"category_scores_gemma":[0.001144607,0.0004591373,0.0009891528,0.001973768,0.0006688996,0.002262637,0.0006825314,0.0009045484,0.003273107],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005619196,"about_ca_system_score_gemma":0.0006389094,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001411798,"about_ca_topic_score_gemma":0.001236507,"domain_scores_codex":[0.9989579,0.00009348394,0.00006356535,0.0002303345,0.0005848155,0.00006989716],"domain_scores_gemma":[0.9993317,0.0001214341,0.00004541889,0.0001222701,0.0003505657,0.00002856674],"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":[0.0002246424,0.000135383,0.0006259485,0.0005817408,0.0001230378,0.0002264418,0.000143947,0.002950086,0.2201939,0.01952083,0.01068548,0.7445885],"study_design_scores_gemma":[0.0002736261,0.001006355,0.005991459,0.000113787,0.0003503907,0.007290548,0.0002364382,0.3188815,0.4638554,0.0217714,0.1797218,0.0005072413],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004026989,0.0009567797,0.9894638,0.0001520249,0.0002546856,0.000161684,0.00009671439,0.001376764,0.003510596],"genre_scores_gemma":[0.05153799,0.0008784118,0.9362403,0.0002096635,0.000239637,0.0002081897,0.00031361,0.0001955051,0.0101767],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00403484,"threshold_uncertainty_score":0.01349789,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01345523164265425,"score_gpt":0.2710841252711502,"score_spread":0.257628893628496,"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."}}