Toward feature space adversarial attack in the frequency domain
Sign Up to like & getrecommendations! Published in 2022 at "International Journal of Intelligent Systems"
DOI: 10.1002/int.23031
Abstract: Recent researchers have shown that deep neural networks (DNNs) are vulnerable to adversarial exemplars, making them unsuitable for security‐critical applications. Transferability of adversarial examples is crucial for attacking black‐box models, which facilitates adversarial attacks in… read more here.
Keywords: frequency domain; space; adversarial attack; feature space ... See more keywords
Facial-expression recognition based on a low-dimensional temporal feature space
Sign Up to like & getrecommendations! Published in 2017 at "Multimedia Tools and Applications"
DOI: 10.1007/s11042-017-5354-x
Abstract: This paper suggests a facial-expression recognition in accordance with face video sequences based on a newly low-dimensional feature space proposed. Indeed, we extract a Pyramid of uniform Temporal Local Binary Pattern representation, using only XT… read more here.
Keywords: facial expression; feature space; low dimensional; feature ... See more keywords
A Modified Support Vector Regression Approach for Failure Analysis in Beam-Like Structures
Sign Up to like & getrecommendations! Published in 2018 at "Journal of Failure Analysis and Prevention"
DOI: 10.1007/s11668-018-0494-5
Abstract: Natural frequency and mode shape differences play a vital role to distinguish between healthy and unhealthy structures. As per the proposed method, the unhealthy structure leads to crack identification in terms of the location and… read more here.
Keywords: feature space; vector regression; regression; support vector ... See more keywords
Feature space learning model
Sign Up to like & getrecommendations! Published in 2019 at "Journal of ambient intelligence and humanized computing"
DOI: 10.1007/s12652-018-0805-4
Abstract: With the massive volume and rapid increasing of data, feature space study is of great importance. To avoid the complex training processes in deep learning models which project original feature space into low-dimensional ones, we… read more here.
Keywords: feature space; feature spaces; feature; model ... See more keywords
Study of the desertification index based on the albedo-MSAVI feature space for semi-arid steppe region
Sign Up to like & getrecommendations! Published in 2019 at "Environmental Earth Sciences"
DOI: 10.1007/s12665-019-8111-9
Abstract: Desertification has been listed as the top of ten major problems affecting global environmental changes, and represents one of the important reasons of semi-arid grassland degradation. It is therefore crucial to understand ecological environment of… read more here.
Keywords: index; feature space; desertification; semi arid ... See more keywords
Cluster analysis of mixed data based on Feature Space Instance Cluster Closeness Metric
Sign Up to like & getrecommendations! Published in 2021 at "Chemometrics and Intelligent Laboratory Systems"
DOI: 10.1016/j.chemolab.2021.104370
Abstract: Abstract Clustering Algorithms have recently attracted considerable attention in machine learning applications due to their high efficiency. However, the existing clustering methods still have some issues that need to be further solved. For example, most… read more here.
Keywords: cluster closeness; feature space; space instance; instance cluster ... See more keywords
Guiding exploration in conformational feature space with Lipschitz underestimation for ab-initio protein structure prediction
Sign Up to like & getrecommendations! Published in 2018 at "Computational biology and chemistry"
DOI: 10.1016/j.compbiolchem.2018.02.003
Abstract: Computing conformations which are essential to associate structural and functional information with gene sequences, is challenging due to the high dimensionality and rugged energy surface of the protein conformational space. Consequently, the dimension of the… read more here.
Keywords: protein; feature space; space; exploration ... See more keywords
Exploring the Influence of Input Feature Space on CNN‐Based Geomorphic Feature Extraction From Digital Terrain Data
Sign Up to like & getrecommendations! Published in 2023 at "Earth and Space Science"
DOI: 10.1029/2023ea002845
Abstract: Many studies of Earth surface processes and landscape evolution rely on having accurate and extensive data sets of surficial geologic units and landforms. Automated extraction of geomorphic features using deep learning provides an objective way… read more here.
Keywords: cnn based; space; feature; input feature ... See more keywords
A data-driven spike sorting feature map for resolving spike overlap in the feature space.
Sign Up to like & getrecommendations! Published in 2021 at "Journal of neural engineering"
DOI: 10.1088/1741-2552/ac0f4a
Abstract: OBJECTIVE Spike sorting is the process of extracting neuronal action potentials, or spikes, from an extracellular brain recording, and assigning each spike to its putative source neuron. Spike sorting is usually treated as a clustering… read more here.
Keywords: feature space; feature; spike sorting; spike overlap ... See more keywords
Stable Iterative Variable Selection.
Sign Up to like & getrecommendations! Published in 2021 at "Bioinformatics"
DOI: 10.1093/bioinformatics/btab501
Abstract: MOTIVATION The emergence of datasets with tens of thousands of features, such as high-throughput omics biomedical data, highlights the importance of reducing the feature space into a distilled subset that can truly capture the signal… read more here.
Keywords: feature space; selection; stable iterative; variable selection ... See more keywords
Generalizable physics-constrained modeling using learning and inference assisted by feature-space engineering
Sign Up to like & getrecommendations! Published in 2021 at "Physical Review Fluids"
DOI: 10.1103/physrevfluids.6.124602
Abstract: This work presents a formalism to improve the predictive accuracy of physical models by learning generalizable augmentations from sparse data. Building on recent advances in data-driven turbulence modeling, the present approach, referred to as Learning… read more here.
Keywords: augmentation; inference; feature space; physics ... See more keywords