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Sensitivity

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Showing 1851–1875 of 2016 papers

TitleStatusHype
Effect of fixation target on the contrast sensitivity in the foveal and parafoveal area—0
Variational Bayesian Inference For A Scale Mixture Of Normal Distributions Handling Missing Data—0
Hierarchical internal representation of spectral features in deep convolutional networks trained for EEG decoding—0
Detection of Tooth caries in Bitewing Radiographs using Deep Learning—0
Calibration of Distributionally Robust Empirical Optimization Models—0
Dynamic Principal Projection for Cost-Sensitive Online Multi-Label Classification—0
Smooth Sensitivity Based Approach for Differentially Private Principal Component Analysis—0
Superpixel Based Segmentation and Classification of Polyps in Wireless Capsule Endoscopy—0
Eigen-Distortions of Hierarchical Representations—0
Shadow Detection With Conditional Generative Adversarial Networks—0
What is the Machine Learning?—0
Monocular Navigation in Large Scale Dynamic Environments—0
Quantifying the Effects of Text Duplication on Semantic Models—0
Deep Learning to Improve Breast Cancer Early Detection on Screening MammographyCode1
Optimization of Ensemble Supervised Learning Algorithms for Increased Sensitivity, Specificity, and AUC of Population-Based Colorectal Cancer Screenings—0
Output Reachable Set Estimation and Verification for Multi-Layer Neural Networks—0
Explicit expressions for European option pricing under a generalized skew normal distribution—0
NMR microscopy for in vivo metabolomics, digitally twinned by computational systems biology, needs a sensitivity boost—0
A Family of Metrics for Clustering Algorithms—0
A Deep Learning Approach to Digitally Stain Optical Coherence Tomography Images of the Optic Nerve Head—0
Multidimensional classification of hippocampal shape features discriminates Alzheimer's disease and mild cognitive impairment from normal aging—0
Brain activity mapping from MEG data via a hierarchical Bayesian algorithm with automatic depth weighting: sensitivity and specificity analysis—0
Coexistence of critical sensitivity and subcritical specificity can yield optimal population coding—0
Recognizing Abnormal Heart Sounds Using Deep Learning—0
Generalised Dice overlap as a deep learning loss function for highly unbalanced segmentationsCode1
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