„Statistics--Data processing“
Suchergebnisse
10.000+ Treffer
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An autoencoder-based approach for feature engineering in cardiovascular disease prediction
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An interpretable information fusion approach to impute meteorological missing values toward cross-domain intelligent forecasting
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A fully convolutional neural network for fast detection, classification, and segmentation of fabric defects
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Performance evaluation of AI and hybrid-AI models for estimation of evaporation in Lesser Himalayan Valley
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Histogram self-organizing map for cluster detection and visualization
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CrossGCL: cross-view graph contrastive learning with dual tasks for drug recommendation
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Sequential monitoring process for bivariate signed integer-valued autoregressive models
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Operationally convenient and risk efficient two-stage estimation of the mean exponential lifetime under interval censoring
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An efficient claim management assurance system using EPC contract based on improved monarch butterfly optimization models
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A novel Adaptive Neural Network-Based Laplacian of Gaussian (AnLoG) classification algorithm for detecting diabetic retinopathy with colour retinal fundus images
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Geometric deep learning for ionospheric TEC modeling using a temporal graph convolutional network
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A decision framework under probabilistic hesitant fuzzy environment with probability estimation for multi-criteria decision making
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Sequential Neural Joint Estimation for likelihood-free inference
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Retraction Note: Hybrid method for mining rules based on enhanced Apriori algorithm with sequential minimal optimization in healthcare industry
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Joint design and compression of convolutional neural networks as a Bi-level optimization problem
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Efficient deep learning approach for augmented detection of Coronavirus disease
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LSTM-based maneuver detection for resident space object catalog maintenance
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Detection of translucent flesh disorder and automatic grading of mangosteens in multi-view images
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A data science approach to mitigating data challenges in serious gaming
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Correction: Methodological challenges in studying disease processes using observational cohort data