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A Real Application of an Autonomous Industrial Mobile Manipulator within Industrial Context
(MDPI, 2021-05-27)
In modern industry there are still a large number of low added-value processes that can be automated or semi-automated with safe cooperation between robot and human operators. The European SHERLOCK project aims to integrate ...
Brain Mapping of Behavioral Domains Using Multi-Scale Networks and Canonical Correlation Analysis
(Frontiers Media, 2022-06)
Simultaneous mapping of multiple behavioral domains into brain networks remains a major challenge. Here, we shed some light on this problem by employing a combination of machine learning, structural and functional brain ...
Feature Selection for Speech Emotion Recognition in Spanish and Basque: On the Use of Machine Learning to Improve Human-Computer Interaction
(Public Library Science, 2014-10-03)
Study of emotions in human-computer interaction is a growing research area. This paper shows an attempt to select the most significant features for emotion recognition in spoken Basque and Spanish Languages using different ...
Fuzzy classification with distance-based depth prototypes: High-dimensional unsupervised and/or supervised problems
(Elsevier, 2023-11)
Supervised and unsupervised classification is crucial in many areas where different types of data sets are common, such as biology, medicine, or industry, among others. A key consideration is that some units are more typical ...
Dynamic selection of the best base classifier in one versus one
(Elsevier, 2015-05-19)
Class binarization strategies decompose the original multi-class problem into several binary sub-problems. One versus One (OVO) is one of the most popular class binarization techniques, which considers every pair of classes ...
NewOneVersusOneAll method: NOV@
(Elsevier, 2014-04-19)
Binarization strategies decompose the original multi-class dataset into multiple two-class subsets, learning a different binary model for each new
subset. One-vs-All (OVA) and One-vs-One (OVO) are two of the most well-known ...
Undirected cyclic graph based multiclass pair-wise classifier: Classifier number reduction maintaining accuracy
(Elsevier, 2015-08-13)
Supervised Classification approaches try to classify correctly the new unlabelled examples based on a set of well-labelled samples. Nevertheless, some classification methods were formulated for binary classification problems ...
K nearest neighbor equality: giving equal chance to all existing classes
(Elsevier, 2011-07-23)
The nearest neighbor classification method assigns an unclassified point to the class of the nearest case of a set of previously classified points. This rule is independent of the underlying joint distribution of the sample ...
Classifier Subset Selection to construct multi-classifiers by means of estimation of distribution algorithms
(Elsevier, 2015-01-24)
This paper proposes a novel approach to select the individual classifiers to take part in a Multiple-Classifier System. Individual classifier selection is a key step in the development of multi-classifiers. Several works ...
dbcsp: User-friendly R package for Distance-Based Common Spatial Patterns
(The R Foundation, 2022-12-20)
Common Spatial Patterns (CSP) is a widely used method to analyse electroencephalography
(EEG) data, concerning the supervised classification of the activity of brain. More generally, it can
be useful to distinguish between ...