{"id":"W3031288689","doi":"10.3390/rs12111729","title":"Review: Deep Learning on 3D Point Clouds","year":2020,"lang":"en","type":"article","venue":"Remote Sensing","topic":"3D Shape Modeling and Analysis","field":"Engineering","cited_by":367,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"National Natural Science Foundation of China","keywords":"Point cloud; Computer science; Artificial intelligence; Deep learning; Raw data; Segmentation; Representation (politics); Point (geometry); Machine learning; Data mining; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001204891,0.000133399,0.0002331823,0.00003321241,0.00006582643,0.00002287245,0.00005023379,0.00004404119,0.00001833437],"category_scores_gemma":[0.0001311474,0.000132747,0.0001086155,0.0002169686,0.000007338307,0.00002837275,0.00001665311,0.0003153209,0.0002485427],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003461622,"about_ca_system_score_gemma":0.00000441146,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008294787,"about_ca_topic_score_gemma":0.000001416314,"domain_scores_codex":[0.9992817,0.00003715976,0.0001901385,0.0001730168,0.0001224529,0.0001955179],"domain_scores_gemma":[0.9996833,0.00003036888,0.00002516529,0.0001346058,0.00002802237,0.00009857418],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000001720133,8.246991e-7,7.326391e-7,0.0002390633,0.0000299672,0.00001943002,0.0001909647,0.5386908,0.002078056,0.000001046028,0.0006895,0.4580579],"study_design_scores_gemma":[0.00006211913,0.00001607958,0.000001007925,0.0007689726,0.00004736515,0.000006881173,0.00002669441,0.9887928,0.000458916,0.00001503891,0.009654558,0.0001495833],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0370213,0.0260444,0.9157296,0.002810054,0.0002170137,0.0001240839,6.748908e-7,0.001465345,0.01658757],"genre_scores_gemma":[0.9780403,0.006564652,0.01194096,0.00302366,0.000316596,4.926743e-9,0.000007416752,0.00005551181,0.00005091161],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.941019,"threshold_uncertainty_score":0.5413263,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01618435042585307,"score_gpt":0.2239378541802312,"score_spread":0.2077535037543781,"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."}}