{"id":"W2612382424","doi":"10.1109/wacv.2017.87","title":"Deep Object Ranking for Template Matching","year":2017,"lang":"en","type":"article","venue":"","topic":"Advanced Neural Network Applications","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Computer science; Ranking (information retrieval); Artificial intelligence; Template matching; Matching (statistics); Object (grammar); Object detection; Pattern recognition (psychology); Computer vision; Image (mathematics); Mathematics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001881696,0.001909017,0.001811431,0.003411658,0.0006087999,0.001882463,0.002618226,0.001840526,0.01004135],"category_scores_gemma":[0.00410958,0.0005204495,0.001311255,0.002230523,0.0005220267,0.002753504,0.001619379,0.001197795,0.005250196],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001742586,"about_ca_system_score_gemma":0.001298088,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007567387,"about_ca_topic_score_gemma":0.01157907,"domain_scores_codex":[0.9976146,0.0003679809,0.0001263094,0.0005884031,0.0009598869,0.0003428657],"domain_scores_gemma":[0.9981464,0.0004946932,0.0001784311,0.0005581374,0.0004952011,0.0001270524],"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":[0.0004228269,0.00018705,0.002107489,0.0001877767,0.0001593394,0.00009525537,0.00003663202,0.07089197,0.01867441,0.004700794,0.01715623,0.8853802],"study_design_scores_gemma":[0.00004107143,0.0002145309,0.002552279,0.00002458524,0.00006188916,0.0002088197,0.00003768664,0.9480504,0.03426293,0.006828791,0.007672891,0.00004416198],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08048347,0.002508703,0.8804495,0.0003604695,0.0004170576,0.0003450114,0.001959259,0.02295997,0.01051651],"genre_scores_gemma":[0.514805,0.000683284,0.4631717,0.0004019589,0.0001870023,0.0001855174,0.005973299,0.001040262,0.01355211],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01004135,"threshold_uncertainty_score":0.03359169,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03430910238187781,"score_gpt":0.3156836645765956,"score_spread":0.2813745621947178,"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."}}