Results 161 to 170 of about 6,917,983 (390)
Sensitivity analysis in discrete Bayesian networks [PDF]
, 1997 Enrique Castillo +2 more
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A Tutorial on Learning with Bayesian Networks [PDF]
, 1998 A Bayesian network is a graphical model that encodes probabilistic relationships among variables of interest. When used in conjunction with statistical techniques, the graphical model has several advantages for data analysis. One, because the model encodes dependencies among all variables, it readily handles situations where some data entries are ...
openaire +3 more sources
Bioinspired Tactile Object Identification Leveraging Deep Learning and Soft Body Compliance
Advanced Intelligent Systems, EarlyView.Herein, it is demonstrated that a soft robotic hand, integrated with low‐resolution tactile sensors, can effectively identify a variety of objects with high accuracy by combining multi‐grasp information. Central to this approach is the development of ROSE‐Net, a specialized neural network designed to harness the data from multiple grasps.
Oliver Shorthose +3 more
wiley +1 more source
Explicitly Bayesian Regularizations in Deep Learning [PDF]
arXiv, 2019 Generalization is essential for deep learning. In contrast to previous works claiming that Deep Neural Networks (DNNs) have an implicit regularization implemented by the stochastic gradient descent, we demonstrate explicitly Bayesian regularizations in a specific category of DNNs, i.e., Convolutional Neural Networks (CNNs).
arxiv
Advanced Intelligent Systems, EarlyView.This paper presents a novel Multi‐Distance Spatial‐Temporal Graph Neural Network for detecting anomalies in blockchain transactions. The model combines multi‐distance graph convolutions with adaptive temporal modeling to capture complex patterns in anonymized cryptocurrency networks.
Shiyang Chen +4 more
wiley +1 more source
Coal rock image recognition method based on improved CLBP and receptive field theory
Deep Underground Science and Engineering, Volume 1, Issue 2, Page 165-173, December 2022., 2022 In view of the evident differences between coal and rock in visual attributes such as color, gloss, and texture, the complete local binary pattern (CLBP) image feature descriptor is introduced for coal and rock image recognition, and the original algorithm oversimplifies local texture features by ignoring imaging information from higher‐order pixels ...
Chuanmeng Sun +4 more
wiley +1 more source
Model Multinomial Bayesian Network pada Data Simulasi Curah Hujan
Statistika, 2012 Bayesian Networks is one of simple Probabilistic Graphical Models are built from theory of bayes probability and graph theory. Probability theory Is directly related to data while graph theory directly related to the form representation to be obtained ...
Nanda Arista Rizki +2 more
doaj
Parametric structure of probabilities in Bayesian networks [PDF]
, 1995 Enrique Castillo +2 more
openalex +1 more source
Advanced Intelligent Systems, EarlyView.A tactile sensor array simultaneously integrates super‐resolution and rapid response capabilities to perceive subtle and dynamic stimuli, mimicking the location‐sensing mechanism of human skin. It effectively and swiftly detects and localizes these stimuli, resulting in a localization inference with a root mean square error of 1.50 mm, and can track ...
Shuyao Zhou +9 more
wiley +1 more source
Combining Bayesian Belief Networks With Gas Path Analysis for Test Cell Diagnostics and Overhaul [PDF]
, 1998 Carl A. Palmer
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