{"id":"W2890848214","doi":"10.1109/icassp.2018.8462291","title":"A Graph-CNN for 3D Point Cloud Classification","year":2018,"lang":"en","type":"article","venue":"","topic":"Advanced Graph Neural Networks","field":"Computer Science","cited_by":181,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Upsampling; Point cloud; Graph; Pooling; Theoretical computer science; Convolutional neural network; Topological graph theory; Artificial intelligence; Line graph; Voltage graph","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":[0.0002342178,0.001085861,0.0004828852,0.00089353,0.0003545006,0.0006002663,0.001888563,0.001062617,0.004688013],"category_scores_gemma":[0.000656762,0.0004864888,0.0009444162,0.001038244,0.0003993043,0.001329247,0.000950749,0.0009382421,0.002047277],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001269068,"about_ca_system_score_gemma":0.0008349681,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02502212,"about_ca_topic_score_gemma":0.03112238,"domain_scores_codex":[0.9997719,0.0000142817,0.000008150732,0.00008567141,0.00007700722,0.0000430939],"domain_scores_gemma":[0.9998366,0.00002122162,0.00001310181,0.00004306517,0.00006577943,0.00002023865],"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":[0.0002441888,0.000160406,0.002428795,0.0001600023,0.0001661875,0.0003035523,0.0000413442,0.3013763,0.05114419,0.009622886,0.03096693,0.6033852],"study_design_scores_gemma":[0.000006477249,0.00003158646,0.0005062854,0.000006123144,0.00001349187,0.00005437151,0.000005822415,0.9856778,0.008353881,0.002488495,0.002845865,0.000009682749],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.04501226,0.0006922372,0.9299968,0.0006236986,0.0003470636,0.0001902157,0.002400018,0.01418266,0.006555127],"genre_scores_gemma":[0.4520878,0.0007838304,0.5245522,0.000605597,0.0001072751,0.0002128447,0.00810577,0.0004358033,0.01310889],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02502212,"threshold_uncertainty_score":0.04975295,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03146337179556759,"score_gpt":0.2832721333078607,"score_spread":0.2518087615122931,"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."}}