State-of-the-art in artificial neural network applications: A survey
This is a survey of neural network applications in the real-world scenario. It provides a
taxonomy of artificial neural networks (ANNs) and furnish the reader with knowledge of …
taxonomy of artificial neural networks (ANNs) and furnish the reader with knowledge of …
SciClone: inferring clonal architecture and tracking the spatial and temporal patterns of tumor evolution
The sensitivity of massively-parallel sequencing has confirmed that most cancers are
oligoclonal, with subpopulations of neoplastic cells harboring distinct mutations. A fine …
oligoclonal, with subpopulations of neoplastic cells harboring distinct mutations. A fine …
Big data analytics for intrusion detection system: Statistical decision-making using finite dirichlet mixture models
N Moustafa, G Creech, J Slay - Data Analytics and Decision Support for …, 2017 - Springer
An intrusion detection system has become a vital mechanism to detect a wide variety of
malicious activities in the cyber domain. However, this system still faces an important …
malicious activities in the cyber domain. However, this system still faces an important …
Outlier dirichlet mixture mechanism: Adversarial statistical learning for anomaly detection in the fog
Current anomaly detection systems (ADSs) apply statistical and machine learning
algorithms to discover zero-day attacks, but such algorithms are vulnerable to advanced …
algorithms to discover zero-day attacks, but such algorithms are vulnerable to advanced …
[图书][B] Background modeling and foreground detection for video surveillance
Background modeling and foreground detection are important steps in video processing
used to detect robustly moving objects in challenging environments. This requires effective …
used to detect robustly moving objects in challenging environments. This requires effective …
A Linear Dirichlet Mixture Model for decomposing scenes: Application to analyzing urban functional zonings
X Zhang, S Du - Remote Sensing of Environment, 2015 - Elsevier
Urban scenes are fundamental to assessing urban landscapes and analyzing the spatial
arrangements of functional zonings. Thus, it is important to obtain the information on urban …
arrangements of functional zonings. Thus, it is important to obtain the information on urban …
A novel statistical approach for clustering positive data based on finite inverted beta-liouville mixture models
C Hu, W Fan, JX Du, N Bouguila - Neurocomputing, 2019 - Elsevier
Nowadays, a great number of positive data has been occurred naturally in many
applications, however, it was not adequately analyzed. In this article, we propose a novel …
applications, however, it was not adequately analyzed. In this article, we propose a novel …
Bayesian estimation of Dirichlet mixture model with variational inference
In statistical modeling, parameter estimation is an essential and challengeable task.
Estimation of the parameters in the Dirichlet mixture model (DMM) is analytically intractable …
Estimation of the parameters in the Dirichlet mixture model (DMM) is analytically intractable …
Designing an online and reliable statistical anomaly detection framework for dealing with large high-speed network traffic
N Moustafa - 2017 - unsworks.unsw.edu.au
Abstract Despite a Network Anomaly Detection System (NADS) being capable of detecting
existing and zero-day attacks, it is still not universally implemented in industry and real …
existing and zero-day attacks, it is still not universally implemented in industry and real …
Variational Bayesian learning of generalized Dirichlet-based hidden Markov models applied to unusual events detection
E Epaillard, N Bouguila - IEEE transactions on neural networks …, 2018 - ieeexplore.ieee.org
Learning a hidden Markov model (HMM) is typically based on the computation of a
likelihood which is intractable due to a summation over all possible combinations of states …
likelihood which is intractable due to a summation over all possible combinations of states …