{"id":"W3186499362","doi":"10.18280/ts.380324","title":"Forest Fire Recognition Based on Feature Extraction from Multi-View Images","year":2021,"lang":"en","type":"article","venue":"Traitement du signal","topic":"Fire Detection and Safety Systems","field":"Engineering","cited_by":147,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Artificial intelligence; Preprocessor; Pattern recognition (psychology); Feature (linguistics); Feature extraction; Hue; Segmentation; Similarity (geometry); Computer vision; Image (mathematics)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002388064,0.000800111,0.00066243,0.001807385,0.0002215258,0.0005326934,0.0005818282,0.0005401181,0.0009604366],"category_scores_gemma":[0.0006170656,0.0002983732,0.0008907566,0.001012688,0.0002622996,0.001070254,0.0004449242,0.0005816153,0.0004839683],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003419125,"about_ca_system_score_gemma":0.0003341123,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003623147,"about_ca_topic_score_gemma":0.004855215,"domain_scores_codex":[0.9996555,0.00002693534,0.00001804873,0.0001300664,0.0001228748,0.00004663193],"domain_scores_gemma":[0.9997799,0.00003701743,0.00004273385,0.00003902876,0.00008083655,0.00002047829],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003353924,0.0001555073,0.00578195,0.000168734,0.0001196067,0.0003873846,0.00008505346,0.03152497,0.1893151,0.001136918,0.001772694,0.7692168],"study_design_scores_gemma":[0.00002026613,0.0001664612,0.01893514,0.00002706596,0.0001303658,0.000931227,0.00009591984,0.8622407,0.1130175,0.00190256,0.002471506,0.00006132328],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1143462,0.0006664672,0.8799564,0.0000884793,0.00009253426,0.0000947573,0.0002796468,0.001824421,0.002651192],"genre_scores_gemma":[0.7354389,0.0008092762,0.2608039,0.0001003284,0.00005648072,0.00006838419,0.0005741222,0.00009161966,0.002057012],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003623147,"threshold_uncertainty_score":0.007204115,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01955420345335343,"score_gpt":0.2237653851795965,"score_spread":0.204211181726243,"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."}}