{"id":"W3144183659","doi":"10.18280/ts.380119","title":"Feature Extraction and Retrieval of Ecommerce Product Images Based on Image Processing","year":2021,"lang":"en","type":"article","venue":"Traitement du signal","topic":"Industrial Vision Systems and Defect Detection","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Feature extraction; Feature (linguistics); Artificial intelligence; Image retrieval; Pattern recognition (psychology); Product (mathematics); Image processing; Metric (unit); Information retrieval; Computer vision; Data mining; Image (mathematics); Mathematics; Engineering","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":[0.0002552849,0.0001193915,0.0001579553,0.0000797581,0.0000651648,0.00005837086,0.00002921217,0.00006809293,0.00009741854],"category_scores_gemma":[0.000029065,0.0001114127,0.00004452608,0.0001994382,0.00001676867,0.0001516605,0.000006384414,0.0001787818,0.000003278388],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003956697,"about_ca_system_score_gemma":0.00002715515,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002930866,"about_ca_topic_score_gemma":0.000001047592,"domain_scores_codex":[0.9992595,0.00004748999,0.0001781046,0.0001774338,0.0002132456,0.0001241775],"domain_scores_gemma":[0.9996747,0.0000389122,0.00005420765,0.0001001388,0.00009225801,0.00003971753],"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":[0.0001448467,0.00006551079,0.0001513559,0.0003158317,0.00002014395,0.00001731326,0.00008969245,0.004309876,0.9503637,0.000007766037,0.003235413,0.04127854],"study_design_scores_gemma":[0.0009867715,0.0001613349,0.005576582,0.000219427,0.00003190732,0.00002670894,0.000135197,0.03145587,0.9545273,0.000007505562,0.00668311,0.0001882495],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9627222,0.0008212529,0.0277621,0.0007338893,0.000652845,0.0005893855,0.00004587051,0.0003101674,0.006362307],"genre_scores_gemma":[0.9988168,0.000008071739,0.0007763766,0.00002505563,0.0002291716,0.000005027992,0.00001161071,0.00001881303,0.0001090812],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04109029,"threshold_uncertainty_score":0.4543278,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01401999636485305,"score_gpt":0.2446550609404732,"score_spread":0.2306350645756201,"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."}}