{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001835685,0.0001371473,0.0001822273,0.0001440369,0.0001778579,0.00004588365,0.0005676976,0.00008556376,0.000004233937],"category_scores_gemma":[0.000001964753,0.000124729,0.00006903625,0.0006224963,0.0001201453,0.0001412601,0.0001320263,0.0001461459,0.0000197452],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002843618,"about_ca_system_score_gemma":0.00007754973,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002911778,"about_ca_topic_score_gemma":1.293392e-7,"domain_scores_codex":[0.9990067,0.000057243,0.0002036768,0.0004082968,0.0001690067,0.0001550004],"domain_scores_gemma":[0.9989542,0.0001548669,0.0001244197,0.0005025662,0.0001877969,0.000076122],"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":[0.00004857347,0.0006509268,0.0001746652,0.0001134615,0.00003006302,0.000008847655,0.0005496191,0.000008850989,0.6669611,0.05158802,0.01186827,0.2679977],"study_design_scores_gemma":[0.0004593531,0.000148993,0.003868256,0.00002072256,0.00001010759,0.00008796031,0.000004840769,0.04267588,0.7177032,0.001250231,0.2335127,0.0002577722],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0003392714,0.00006367053,0.9961149,0.001994331,0.000007473304,0.0005298751,0.00001311923,0.0002253802,0.0007119983],"genre_scores_gemma":[0.01029703,0.0000227987,0.9886054,0.0006515224,0.00004381406,0.00008574081,0.000009247534,0.000009745718,0.000274642],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.2677399,"threshold_uncertainty_score":0.5086302,"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."}}