{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002962126,0.0005625801,0.000580612,0.001923815,0.0001960091,0.0005836255,0.0004746024,0.0005354334,0.0009261867],"category_scores_gemma":[0.0007265948,0.0001833103,0.0007826664,0.001382538,0.0002706788,0.0009653139,0.0002691628,0.0004204143,0.0004553283],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003202168,"about_ca_system_score_gemma":0.0002870883,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002198208,"about_ca_topic_score_gemma":0.00189049,"domain_scores_codex":[0.9997368,0.00002247455,0.00002036107,0.00006357186,0.0001200579,0.00003673805],"domain_scores_gemma":[0.9997703,0.00004837164,0.00002708191,0.00003181658,0.0001110273,0.00001131952],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002310294,0.0001216182,0.00181265,0.0001885312,0.00006226023,0.0002447503,0.00008583484,0.00943579,0.2086714,0.001623681,0.002324922,0.7751976],"study_design_scores_gemma":[0.00004075007,0.0004944045,0.02942628,0.00002894216,0.0001809926,0.001275631,0.0001473706,0.7396127,0.2184187,0.002410971,0.007887891,0.00007525361],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1397563,0.001156659,0.8529633,0.0002208824,0.0001199052,0.000177441,0.000220803,0.001463506,0.003921072],"genre_scores_gemma":[0.5718423,0.0009910987,0.4218968,0.000144596,0.0001162139,0.0001111838,0.0005349336,0.00008967952,0.004273196],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002198208,"threshold_uncertainty_score":0.004370868,"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."}}