{"id":"W3112100457","doi":"10.1109/smc42975.2020.9283377","title":"TentNet: Deep Learning Tent Detection Algorithm Using A Synthetic Training Approach","year":2020,"lang":"en","type":"article","venue":"","topic":"Flood Risk Assessment and Management","field":"Environmental Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lakehead University","funders":"","keywords":"Computer science; Artificial intelligence; Deep learning; Transfer of learning; Adversarial system; Machine learning; Baseline (sea); Architecture; Class (philosophy); Generative grammar; Satellite imagery; Satellite; Image (mathematics); Remote sensing; Engineering; Geography","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":[0.0006814539,0.001003167,0.0004565367,0.0006419286,0.0002834722,0.0005433816,0.001195633,0.001008064,0.00244304],"category_scores_gemma":[0.001692705,0.0003079837,0.0004610731,0.0003878826,0.0004867421,0.0008475439,0.000934147,0.001132538,0.0007443762],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008591409,"about_ca_system_score_gemma":0.0008831262,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005715478,"about_ca_topic_score_gemma":0.007674193,"domain_scores_codex":[0.9998277,0.00003571096,0.000008819252,0.00004904473,0.00004361762,0.00003507537],"domain_scores_gemma":[0.999642,0.0001212858,0.00004007712,0.00006083939,0.0001059322,0.0000298188],"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":[0.0002898984,0.0001547247,0.003553153,0.00008916771,0.00007859461,0.0001935354,0.000070062,0.7209175,0.006000095,0.005777132,0.01371963,0.2491565],"study_design_scores_gemma":[0.000008605934,0.00004385212,0.0001835097,0.000007634068,0.00000434182,0.00003051767,0.00001194336,0.9947901,0.002035871,0.001735955,0.001143025,0.000004608999],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1853239,0.000815579,0.7888797,0.001128969,0.000375515,0.0002551561,0.001492126,0.009621539,0.01210753],"genre_scores_gemma":[0.7364943,0.0002508425,0.2473916,0.000482319,0.00007147788,0.0002557882,0.003881983,0.0002754972,0.01089634],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005715478,"threshold_uncertainty_score":0.01136446,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03109738833071552,"score_gpt":0.2253259938248429,"score_spread":0.1942286054941273,"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."}}