{"id":"W3186788152","doi":"10.18280/ts.380322","title":"Automatic Extraction of Color Features from Landscape Images Based on Image Processing","year":2021,"lang":"en","type":"article","venue":"Traitement du signal","topic":"Remote Sensing and Land Use","field":"Earth and Planetary Sciences","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Artificial intelligence; Computer vision; Computer science; Color image; Color quantization; Color space; Color balance; False color; Color histogram; Image processing; Support vector machine; Pattern recognition (psychology); Color correction; Image (mathematics)","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001360258,0.0001087498,0.0001551933,0.00005261843,0.00009573361,0.00008703853,0.00006211204,0.0000440106,0.004602344],"category_scores_gemma":[0.00002398197,0.0000821107,0.00005654315,0.0001219702,0.00003054462,0.0001177548,0.000002333669,0.00009509313,0.00003101066],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000002984163,"about_ca_system_score_gemma":0.00007256676,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003023323,"about_ca_topic_score_gemma":0.0002350363,"domain_scores_codex":[0.9991064,0.00008265029,0.0001853933,0.0001937169,0.000280115,0.0001517021],"domain_scores_gemma":[0.9995204,0.0001742174,0.00009502163,0.00009816951,0.00005344138,0.00005878858],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0003908318,0.0003546039,0.05782249,0.0002317485,0.00007239372,0.0003089697,0.0007157887,0.02006213,0.04717714,0.000004516034,0.007188883,0.8656705],"study_design_scores_gemma":[0.0005834658,0.0001372656,0.5851393,0.0001178443,0.0000364948,0.000008369444,0.0001950319,0.3955827,0.01765774,0.00004948964,0.0003716968,0.0001206686],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9911337,0.0002708588,0.0007228845,0.0003435375,0.0001194052,0.00008453633,0.00009741812,0.00005515747,0.007172455],"genre_scores_gemma":[0.9937943,0.000008554725,0.005492555,0.0002144067,0.0001168673,2.026256e-7,0.0002879312,0.000003609374,0.00008160098],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8655499,"threshold_uncertainty_score":0.9963076,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009783556445075085,"score_gpt":0.2239966820179179,"score_spread":0.2142131255728428,"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."}}