{"id":"W2118283163","doi":"10.1109/igarss.2007.4423938","title":"New object-oriented approach for urban objects extraction from VHSR images","year":2007,"lang":"en","type":"article","venue":"","topic":"Remote-Sensing Image Classification","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Computer science; Pixel; Artificial intelligence; Multispectral image; Computer vision; Object (grammar); Ground truth; Segmentation; Image resolution; Image segmentation; Object detection; Base (topology); Fuzzy logic; Pattern recognition (psychology); Mathematics","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":[0.0001761256,0.0001704039,0.0001467476,0.0001185668,0.00005697916,0.00005946105,0.00008290723,0.0001250771,0.00003438558],"category_scores_gemma":[0.0000895031,0.00017372,0.00006935724,0.0002070681,0.00001663803,0.0002637724,0.000009072509,0.0001369782,0.00004252788],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001423818,"about_ca_system_score_gemma":0.00002188598,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000142068,"about_ca_topic_score_gemma":0.00002629035,"domain_scores_codex":[0.9990179,0.000009854218,0.0002550284,0.0002694355,0.0001537243,0.0002940714],"domain_scores_gemma":[0.9993153,0.0001425991,0.00004399768,0.0003125116,0.0000698029,0.0001157931],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00005254254,0.00004608097,0.0002436866,0.00004478456,0.00006365647,0.000003513481,0.0005159401,0.002781703,0.850198,0.000204688,0.06930541,0.07654004],"study_design_scores_gemma":[0.0008197343,0.00003404484,0.01577263,0.00001748401,0.00004813975,0.000009513983,0.0005297296,0.2286206,0.7377993,0.000165898,0.015774,0.0004089177],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01075244,0.0001357971,0.9449503,0.00002626765,0.0005763176,0.0003468474,0.000006184989,0.000815284,0.04239051],"genre_scores_gemma":[0.5941386,0.000008010751,0.4019395,0.00002282534,0.0004829207,0.000003656236,0.0001378604,0.00005426455,0.003212329],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5833862,"threshold_uncertainty_score":0.7084098,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01442929650805727,"score_gpt":0.2450042219127678,"score_spread":0.2305749254047105,"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."}}