{"id":"W4413061107","doi":"10.3390/electronics14142874","title":"Deep Learning for Computer Vision Application","year":2025,"lang":"en","type":"article","venue":"Electronics","topic":"Advanced Neural Network Applications","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada; Public Safety Canada","funders":"","keywords":"Deep learning; Artificial intelligence; Computer science; Artificial neural network; Deep neural networks; Machine learning; Human–computer interaction","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":[0.0005062179,0.0005846833,0.0004453116,0.0006438522,0.000275732,0.001409615,0.0009942359,0.001250168,0.01640524],"category_scores_gemma":[0.001955784,0.0002462237,0.00033709,0.001232451,0.0004790433,0.00147844,0.00101249,0.002302175,0.009238361],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008676982,"about_ca_system_score_gemma":0.0008726727,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002024323,"about_ca_topic_score_gemma":0.001880262,"domain_scores_codex":[0.99955,0.00004902512,0.00002361489,0.00009466436,0.0002406161,0.00004202356],"domain_scores_gemma":[0.9994844,0.0001185835,0.00003836049,0.00008311388,0.0002437063,0.00003188061],"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":[0.00007775924,0.000072371,0.0004991888,0.0006628011,0.00004818424,0.00008665021,0.00004986297,0.02652379,0.01103151,0.1429401,0.1187891,0.6992186],"study_design_scores_gemma":[0.00002084519,0.00007822662,0.0009302523,0.0003845158,0.00002726676,0.0002400195,0.00004295316,0.3200613,0.01342656,0.206999,0.4577398,0.00004916955],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004729644,0.03269177,0.877037,0.005818175,0.001365518,0.0001669718,0.001288214,0.004588935,0.07231385],"genre_scores_gemma":[0.2893322,0.05609788,0.5323252,0.004174173,0.001888152,0.0005638303,0.005553741,0.001183299,0.1088816],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01640524,"threshold_uncertainty_score":0.05488104,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005766111807368011,"score_gpt":0.2752802122171564,"score_spread":0.2695141004097883,"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."}}