{"id":"W3119842544","doi":"10.18280/ts.370622","title":"A Novel Convolutional Neural Network Based Model for Recognition and Classification of Apple Leaf Diseases","year":2020,"lang":"en","type":"article","venue":"Traitement du signal","topic":"Smart Agriculture and AI","field":"Agricultural and Biological Sciences","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Convolutional neural network; Sustenance; Computer science; Cluster analysis; Contrast (vision); Artificial intelligence; Identification (biology); Artificial neural network; Pattern recognition (psychology); Set (abstract data type); Fuzzy logic; Machine learning; Data mining; Botany; Biology","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":[0.0002274457,0.0006085618,0.0003890089,0.0004368271,0.000249839,0.0005071578,0.0009207539,0.0007451355,0.001447757],"category_scores_gemma":[0.0003212607,0.0002352031,0.0005571603,0.0002795529,0.0001700366,0.0004412447,0.0002839229,0.0005972104,0.0004354066],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008005625,"about_ca_system_score_gemma":0.0007527471,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02853995,"about_ca_topic_score_gemma":0.02718699,"domain_scores_codex":[0.9999012,0.000007247985,0.000006629359,0.00003506797,0.00002160673,0.00002829467],"domain_scores_gemma":[0.999911,0.00001951552,0.00001002372,0.000006489535,0.00004660463,0.00000641672],"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":[0.0003824407,0.0003412529,0.008789492,0.0001467072,0.0002165111,0.0002728286,0.00006538819,0.6593714,0.04332642,0.002006748,0.004506575,0.2805742],"study_design_scores_gemma":[0.000002801445,0.00002680031,0.0007847727,0.000004957918,0.00001280523,0.0000172337,0.000002658732,0.9966493,0.002036287,0.0001471396,0.0003112113,0.000004042878],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.3123702,0.002792785,0.6664779,0.0009119894,0.0005219391,0.0002022459,0.001388634,0.003685552,0.01164876],"genre_scores_gemma":[0.9417356,0.0006530329,0.04413486,0.000189895,0.0000474062,0.0001398486,0.001081343,0.00003345858,0.01198458],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02853995,"threshold_uncertainty_score":0.05674767,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08853861807156183,"score_gpt":0.2224660641871516,"score_spread":0.1339274461155897,"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."}}