{"id":"W4400041543","doi":"10.18280/ts.410347","title":"A Compare Research of Two Different Point Clouds 3D Object Detection Methods","year":2024,"lang":"en","type":"article","venue":"Traitement du signal","topic":"Advanced Neural Network Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Xi'an Municipal Bureau of Science and Technology","keywords":"Point cloud; Computer science; Artificial intelligence; Robustness (evolution); Partition (number theory); Classifier (UML); Deep learning; Pattern recognition (psychology); Artificial neural network; Object detection; Computer vision; Data mining; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002329266,0.002492194,0.001957191,0.006836745,0.0007484201,0.002485249,0.002781533,0.002049233,0.002908879],"category_scores_gemma":[0.005239749,0.0007867237,0.002048022,0.003269571,0.0005945748,0.003274036,0.001801333,0.001344391,0.001602396],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001601443,"about_ca_system_score_gemma":0.001385233,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01793071,"about_ca_topic_score_gemma":0.01388285,"domain_scores_codex":[0.9942977,0.000402795,0.000310432,0.001591859,0.002864247,0.0005329567],"domain_scores_gemma":[0.997317,0.0006450683,0.0001322873,0.0003860149,0.001361195,0.0001583956],"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":[0.001223802,0.0003627113,0.01026723,0.0008074024,0.0006893701,0.0001897276,0.000117009,0.03530549,0.01946654,0.00233615,0.01266956,0.9165649],"study_design_scores_gemma":[0.0001338284,0.0007931776,0.02154413,0.0001479644,0.0003105233,0.0007825101,0.0002999864,0.907704,0.0501676,0.002166304,0.01578655,0.0001634673],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2863995,0.0216523,0.6503811,0.001215695,0.002673367,0.0009788346,0.005600828,0.01392894,0.01716954],"genre_scores_gemma":[0.5434874,0.005976913,0.423299,0.0005233681,0.0003791335,0.0004827401,0.0144007,0.0007689635,0.01068177],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01793071,"threshold_uncertainty_score":0.0356527,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09885877208109599,"score_gpt":0.4253778085073617,"score_spread":0.3265190364262657,"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."}}