{"id":"W4385801120","doi":"10.1109/cvprw59228.2023.00558","title":"Robust and Scalable Vehicle Re-Identification via Self-Supervision","year":2023,"lang":"en","type":"article","venue":"","topic":"Video Surveillance and Tracking Methods","field":"Computer Science","cited_by":32,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Computer science; Scalability; Software deployment; Overhead (engineering); Identification (biology); Code (set theory); Machine learning; Focus (optics); Artificial intelligence; State (computer science); Resource (disambiguation); Simple (philosophy); Data mining; Distributed computing; Database; Software engineering; Algorithm; Programming language","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":[0.0008495204,0.001421621,0.001298827,0.0008306642,0.0005386403,0.0008358287,0.002982392,0.001131083,0.002634558],"category_scores_gemma":[0.002869058,0.0007123157,0.0006310549,0.0006731748,0.0005743562,0.002199718,0.00240018,0.001740576,0.003490826],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005195004,"about_ca_system_score_gemma":0.001355282,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007371448,"about_ca_topic_score_gemma":0.01362557,"domain_scores_codex":[0.9989868,0.0001127854,0.00002963386,0.0004605714,0.0002453129,0.0001649155],"domain_scores_gemma":[0.9984956,0.0002408556,0.0001271582,0.0006603495,0.000405937,0.00007021019],"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":[0.0004377322,0.0003702088,0.005545909,0.0002428273,0.0001529099,0.0002247916,0.0002262897,0.3130051,0.03320513,0.003717392,0.02693457,0.6159372],"study_design_scores_gemma":[0.00001232596,0.00004422204,0.00103244,0.00001283371,0.00001195692,0.0001040467,0.00005763836,0.9836479,0.009631299,0.002886513,0.002543571,0.0000152943],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04886455,0.0003856841,0.9263308,0.0002532381,0.0002140286,0.0001581057,0.0008428872,0.01659202,0.006358701],"genre_scores_gemma":[0.674512,0.0002097001,0.3088097,0.0002745859,0.0001226964,0.0001503996,0.004943973,0.0007002269,0.01027661],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007371448,"threshold_uncertainty_score":0.01465708,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0437965585633666,"score_gpt":0.282335671774227,"score_spread":0.2385391132108604,"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."}}