… contents, ie a feature descriptor algorithm. That is, feature extraction plays the role of an
intermediate image processing stage between different computer vision algorithms. In this work, …

… be extracted from the IoT environment by feature extraction models, which play a significant
… feature extraction algorithms with several ML models. This study evaluated several feature …

… feature selection and feature extraction algorithms, the need arises to count on criteria that
enable to adequately decide which algorithm … different feature selection and feature extraction …

… we propose a novel feature extraction algorithm, referred to as … We briefly review some feature
extraction algorithms that we … used algorithms in the literature for feature extraction. This is …

… algorithms and the respective images used within this work are divided into two groups:
feature-… widely used algorithms are assessed: color histogram, FAST (Features from Accelerated …

… feature extraction techniques that have been explicitly described above. Even though the
selection of a feature extraction algorithm … the selection of any feature extraction algorithm. The …

… selection and extraction from high-dimensionality data sets using genetic algorithms. We …
feature evaluation and classification. That is, we carry out feature selection or feature extraction …

… This paper focuses on the feature extraction component of the algorithm for two-class … of
highly discriminatory features. Two algorithms for finding such feature spaces are proposed: 1) a …

… feature vector and/or reducing its dimensionality. A well-defined feature extraction algorithm
… In this paper, SVM is also investigated and compared to linear feature extraction algorithms. …

… algorithm for feature extraction based on the decision boundary. The algorithm predicts the
minimum number of features … time, the algorithm finds the needed feature vectors. Noting that …