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LRP-Based path relevances for global explanation of deep architectures
(Elsevier B.V., 2020)
Efficient Learning Machines: Theories, Concepts, and Applications for Engineers and System Designers
Machine learning techniques provide cost-effective alternatives to traditional methods for extracting underlying relationships between information and data and for predicting future events by processing existing information ...
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 ...
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 ...
LEARNING SPAM FEATURES USING RESTRICTED BOLTZMANN MACHINES
(Iadis, 2016-01-01)
Nowadays, spam detection has been one of the foremost machine learning-oriented applications in the context of security in computer networks. In this work, we propose to learn intrinsic properties of e-mail messages by ...
Temperature-Based Deep Boltzmann Machines
(Springer, 2018-08-01)
Deep learning techniques have been paramount in the last years, mainly due to their outstanding results in a number of applications, that range from speech recognition to face-based user identification. Despite other ...
Machine Learning and Bayes Probability For Detecting Camouflaged Mini Pandemic at the Waves of Covid-19
(IEEE, 2022)
This paper present a methodology based at Machine Learning and a theory backed by the Bayes probability to identify rare strains that might not be in coherence with the corona virus. By using the criteria of Tom Mitchell ...
Detección de comunicaciones maliciosas a través de Machine Learning y Deep learningDetection of malicious communications through Machine Learning and Deep learning
(Barranquilla, Universidad del Norte, 2021, 2021)