{"id":"W4313528395","doi":"10.1080/2150704x.2022.2163203","title":"R-ProjNet: an optimal rotated-projection neural network for wood segmentation from point clouds","year":2022,"lang":"en","type":"article","venue":"Remote Sensing Letters","topic":"Remote Sensing and LiDAR Applications","field":"Environmental Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"China Postdoctoral Science Foundation; Natural Science Foundation of Jiangsu Province; National Natural Science Foundation of China","keywords":"Point cloud; Projection (relational algebra); Computer science; Artificial intelligence; Segmentation; Preprocessor; Artificial neural network; Computer vision; Convolution (computer science); Laser scanning; Process (computing); Algorithm; Laser; Optics","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":[0.000356421,0.0001887685,0.0001585268,0.00004019601,0.0009143909,0.00007869262,0.000146289,0.0000444879,0.0001534206],"category_scores_gemma":[0.00001236559,0.0002128135,0.00009901485,0.0003321852,0.00008605071,0.0001582698,0.0001107958,0.0002487649,0.00005143945],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004101753,"about_ca_system_score_gemma":0.00001180508,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003767337,"about_ca_topic_score_gemma":0.0001517457,"domain_scores_codex":[0.998197,0.0002158597,0.0002662074,0.000575179,0.0003403639,0.0004054283],"domain_scores_gemma":[0.9992736,0.00007082502,0.0001567149,0.0003942346,0.000009909491,0.00009474215],"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":[0.0001084491,0.0000210053,0.00005881068,0.000001925414,0.0000201637,0.000007875805,0.001054866,0.4701,0.2590971,0.000001660914,0.01161721,0.2579109],"study_design_scores_gemma":[0.000536527,0.0001195896,0.001648831,0.000007145433,0.00005224848,0.00006816052,0.000495881,0.9797434,0.004370211,0.000270142,0.01234994,0.0003379623],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8941901,0.0000084277,0.1010218,0.00308471,0.0005187888,0.0006058885,0.00001665886,0.0001754621,0.0003781343],"genre_scores_gemma":[0.7577171,0.000002134839,0.2367215,0.00439148,0.0005505091,0.000001362802,0.0004270034,0.0000636223,0.0001252721],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5096433,"threshold_uncertainty_score":0.8678282,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01447376400125892,"score_gpt":0.2415373272633763,"score_spread":0.2270635632621174,"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."}}