{"id":"W3183445961","doi":"10.18280/ts.380338","title":"Recognition and Classification of Concrete Cracks under Strong Interference Based on Convolutional Neural Network","year":2021,"lang":"en","type":"article","venue":"Traitement du signal","topic":"Infrastructure Maintenance and Monitoring","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Chongqing Jiaotong University; Division of Graduate Education; Chongqing Municipal Education Commission; National Natural Science Foundation of China","keywords":"Convolutional neural network; Computer science; Pattern recognition (psychology); Block (permutation group theory); Focus (optics); Artificial intelligence; Interference (communication); Layer (electronics); Regularization (linguistics); Algorithm; Mathematics; Channel (broadcasting); Geometry; Materials science; Telecommunications","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":[0.0003048681,0.0008568987,0.0005733666,0.001359036,0.0001977608,0.0004846652,0.0006345326,0.0006272777,0.0006022312],"category_scores_gemma":[0.0005870216,0.0002315411,0.0006080834,0.0005699538,0.0003838002,0.0008436249,0.0005618139,0.0004323301,0.0002144573],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004530948,"about_ca_system_score_gemma":0.0003915361,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008153572,"about_ca_topic_score_gemma":0.01411108,"domain_scores_codex":[0.9997024,0.00002267706,0.00001395293,0.0000909036,0.0000934952,0.00007654777],"domain_scores_gemma":[0.9997794,0.0000439172,0.00004703268,0.00002722853,0.00007846877,0.00002390722],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006878972,0.0002275236,0.02719305,0.0002101755,0.0001709135,0.0007503217,0.0001404377,0.210307,0.1698136,0.002033914,0.003072941,0.5853923],"study_design_scores_gemma":[0.000004918843,0.00008596169,0.009483914,0.0000123119,0.00004043012,0.0001315866,0.00003240179,0.9712381,0.0178912,0.0004174986,0.0006480723,0.00001367203],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5707741,0.001478839,0.4213471,0.0001705359,0.0001510123,0.00007459539,0.0003817228,0.001985986,0.003636053],"genre_scores_gemma":[0.964791,0.0003686475,0.03215844,0.0000547268,0.00003237968,0.00001722397,0.0004930081,0.00002860125,0.002055788],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008153572,"threshold_uncertainty_score":0.01621222,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03046910358376753,"score_gpt":0.2265510533885111,"score_spread":0.1960819498047436,"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."}}