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kappa-Entropy Based Restricted Boltzmann Machines
(Ieee, 2019-01-01)
Restricted Boltzmann Machines achieved notorious popularity in the scientific community in the last decade due to outstanding results in a wide range of applications and also for providing the required mechanisms to build ...
κ-Entropy Based Restricted Boltzmann Machines
(2019-07-01)
Restricted Boltzmann Machines achieved notorious popularity in the scientific community in the last decade due to outstanding results in a wide range of applications and also for providing the required mechanisms to build ...
Machine learning techniques to predict overweight or obesity
(2021-01-01)
Overweight and obesity are considered a public health problem, as they are related to the risk of various diseases, and also to the risk of increased morbidity and mortality. The main objective of this work was to apply ...
Machine Learning for Web Intrusion Detection: A Comparative Analysis of Feature Selection Methods mRMR and PFI
(2020-01-01)
Select from the best features in a complex dataset that is a critical task for machine learning algorithms. This work presents a comparative analysis between two resource selection techniques: Minimum Redundancy Maximum ...
The assessment of the quality of sugar using electronic tongue and machine learning algorithms
(2012-12-01)
The correct classification of sugar according to its physico-chemical characteristics directly influences the value of the product and its acceptance by the market. This study shows that using an electronic tongue system ...
Precipitates segmentation from scanning electron microscope images through machine learning techniques
(2011-06-02)
The presence of precipitates in metallic materials affects its durability, resistance and mechanical properties. Hence, its automatic identification by image processing and machine learning techniques may lead to reliable ...
Flexible Job Shop Problem with Variable Machine Flexibility
(2019-01-01)
We analyze machine flexibility in the context of the flexible job shop problem. In general, the decisions about machine flexibility are taken in advance (the data sets already contain this information). Based on a mathematical ...
Parkinson’s disease identification using restricted Boltzmann machines
(2017-01-01)
Currently, Parkinson’s Disease (PD) has no cure or accurate diagnosis, reaching approximately 60,000 new cases yearly and worldwide, being more often in the elderly population. Its main symptoms can not be easily uncorrelated ...
Learning kernels for support vector machines with polynomial powers of sigmoid
(Ieee, 2014-01-01)
In the pattern recognition research field, Support Vector Machines (SVM) have been an effectiveness tool for classification purposes, being successively employed in many applications. The SVM input data is transformed into ...
The application of distributed virtual machines for enterprise computer management: A two-tier network file system for image provisioning and management
(2008-09-23)
In order to simplify computer management, several system administrators are adopting advanced techniques to manage software configuration of enterprise computer networks, but the tight coupling between hardware and software ...