{"id":"W4387803165","doi":"10.1109/igarss52108.2023.10283369","title":"Instance Segmentation on 3D City Meshes for Building Extraction","year":2023,"lang":"en","type":"article","venue":"","topic":"3D Modeling in Geospatial Applications","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Segmentation; Computer science; Polygon mesh; Scale-space segmentation; Image segmentation; Artificial intelligence; Segmentation-based object categorization; Architecture; Hidden Markov model; Data mining; Pattern recognition (psychology); Machine learning; Computer vision; Computer graphics (images); Geography","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007804157,0.00006052783,0.00004811682,0.00005730702,0.00006785194,0.00001745816,0.00004537719,0.00003362548,0.00002361367],"category_scores_gemma":[0.00001638671,0.00006455729,0.0000206581,0.0001653646,0.000004482401,0.00009085354,0.000005145268,0.00004512348,0.00005757589],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006253565,"about_ca_system_score_gemma":0.000003910607,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000015748,"about_ca_topic_score_gemma":0.00002581496,"domain_scores_codex":[0.9996041,0.000002406982,0.0001042151,0.0001048489,0.00007369742,0.0001107431],"domain_scores_gemma":[0.9997604,0.00007888908,0.00001303601,0.0001032909,0.00002400091,0.00002036731],"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":[0.000003506334,0.000008384939,0.00005520795,0.00002546068,0.000009512045,1.013928e-7,0.00008223106,0.9129236,0.05220757,0.004459515,0.003573655,0.02665121],"study_design_scores_gemma":[0.0001185432,0.00001287841,0.000593379,0.00001044317,0.000005293248,2.385003e-7,0.00003279959,0.9440472,0.04924136,0.002127024,0.003719812,0.00009104419],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1871118,0.000005859158,0.8096787,0.0001087481,0.0001954698,0.0002433282,0.000008560682,0.0008900519,0.001757549],"genre_scores_gemma":[0.8794136,0.0000281552,0.1197839,0.00003615991,0.00008798273,0.0003210219,0.00003615268,0.0000210346,0.0002719876],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6923019,"threshold_uncertainty_score":0.263257,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03521102526170028,"score_gpt":0.3070178034023432,"score_spread":0.2718067781406429,"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."}}