International Conference Image Analysis and Recognition (ICIAR 2018, Póvoa de Varzim, Portugal
Machine learning is used nowadays to build models for classification and regression tasks, among oth...
Data can create enormous values in both scientific and industrial fields, especially for access to n...
Devido ao crescimento do volume de imagens e, consequentemente, da grande quantidade e complexidade ...
[Abstract] In computer vision, current feature extraction techniques generate high dimensional data...
The last decade saw a considerable increase in the availability of data. Unfortunately, this increas...
To date, the world continues to generate quintillion bytes of data daily, leading to the pressing ne...
OF COMPUTER VISION Most learning systems use hand-picked sets of features as input data for their le...
AbstractFeature selection, as a dimensionality reduction technique, aims to choosing a small subset ...
Data dimensionality is growing exponentially, which poses chal-lenges to the vast majority of existi...
Dimension reduction or feature selection is thought to be the backbone of big data applications in o...
Feature selection is an important issue in pattern recognition. The goal of feature selection algori...
Feature selection has been a productive field of research and development in data mining, machine le...
One major component of machine learning is feature analysis which comprises of mainly two processes:...
In many applications, like function approximation, pattern recognition, time series prediction, and ...
The high-dimensionality of Big Data poses challenges in data understanding and visualization. Furthe...
Machine learning is used nowadays to build models for classification and regression tasks, among oth...
Data can create enormous values in both scientific and industrial fields, especially for access to n...
Devido ao crescimento do volume de imagens e, consequentemente, da grande quantidade e complexidade ...
[Abstract] In computer vision, current feature extraction techniques generate high dimensional data...
The last decade saw a considerable increase in the availability of data. Unfortunately, this increas...
To date, the world continues to generate quintillion bytes of data daily, leading to the pressing ne...
OF COMPUTER VISION Most learning systems use hand-picked sets of features as input data for their le...
AbstractFeature selection, as a dimensionality reduction technique, aims to choosing a small subset ...
Data dimensionality is growing exponentially, which poses chal-lenges to the vast majority of existi...
Dimension reduction or feature selection is thought to be the backbone of big data applications in o...
Feature selection is an important issue in pattern recognition. The goal of feature selection algori...
Feature selection has been a productive field of research and development in data mining, machine le...
One major component of machine learning is feature analysis which comprises of mainly two processes:...
In many applications, like function approximation, pattern recognition, time series prediction, and ...
The high-dimensionality of Big Data poses challenges in data understanding and visualization. Furthe...
Machine learning is used nowadays to build models for classification and regression tasks, among oth...
Data can create enormous values in both scientific and industrial fields, especially for access to n...
Devido ao crescimento do volume de imagens e, consequentemente, da grande quantidade e complexidade ...
DOI
Add to ORKG