Results 61 to 70 of about 4,627,177 (313)
Prediction of diabetic protein markers based on an ensemble method
Frontiers in Bioscience-Landmark, 2021 Introduction: A diabetic protein marker is a type of protein that is closely related to diabetes. This kind of protein plays an important role in the prevention and diagnosis of diabetes.
Kaiyang Qu, Quan Zou, Hua Shi
doaj +1 more source
Modal features for image texture classification [PDF]
, 2020 Feature extraction is a key step in image processing for pattern recognition and machine learning processes. Its purpose lies in reducing the dimensionality of the input data through the computing of features which accurately describe the original information.
arxiv +1 more source
Feature Extraction for Functional Time Series: Theory and Application to NIR Spectroscopy Data [PDF]
arXiv, 2021 We propose a novel method to extract global and local features of functional time series. The global features concerning the dominant modes of variation over the entire function domain, and local features of function variations over particular short intervals within function domain, are both important in functional data analysis.
arxiv
On the feature extraction in discrete space [PDF]
Pattern Recognition, 2014 In many pattern recognition applications, feature space expansion is a key step for improving the performance of the classifier. In this paper, we (i) expand the discrete feature space by generating all orderings of values of k discrete attributes exhaustively, (ii) modify the well-known decision tree and rule induction classifiers (ID3, Quilan, 1986 ...
openaire +5 more sources
, 2020 The innovation in science and technical knowledge has prompted an enormous amount of information for the agrarian sector. Machine learning has risen with massive processing techniques to perceive new contingencies in agricultural development.
D. Elavarasan +3 more
semanticscholar +1 more source
Time-space-frequency feature Fusion for 3-channel motor imagery classification [PDF]
arXiv, 2023 Low-channel EEG devices are crucial for portable and entertainment applications. However, the low spatial resolution of EEG presents challenges in decoding low-channel motor imagery. This study introduces TSFF-Net, a novel network architecture that integrates time-space-frequency features, effectively compensating for the limitations of single-mode ...
arxiv
Rethinking Measures of Functional Connectivity via Feature Extraction
Scientific Reports, 2020 Functional magnetic resonance imaging (fMRI)-based functional connectivity (FC) commonly characterizes the functional connections in the brain. Conventional quantification of FC by Pearson's correlation captures linear, time-domain dependencies among ...
R. Mohanty +3 more
semanticscholar +1 more source
Event Arguments Extraction via Dilate Gated Convolutional Neural Network with Enhanced Local Features [PDF]
arXiv, 2020 Event Extraction plays an important role in information-extraction to understand the world. Event extraction could be split into two subtasks: one is event trigger extraction, the other is event arguments extraction. However, the F-Score of event arguments extraction is much lower than that of event trigger extraction, i.e.
arxiv
EMFET: E-mail Features Extraction Tool [PDF]
, 2017 EMFET is an open source and flexible tool that can be used to extract a large number of features from any email corpus with emails saved in EML format. The extracted features can be categorized into three main groups: header features, payload (body) features, and attachment features.
arxiv +1 more source
Color Feature Based Dominant Color Extraction
IEEE Access, 2022 The dominant colors in an image can be used for image search, color editing, palette generation, and several other applications. Conventionally, dominant colors are extracted using clustering or histogram-based methods.
Youngha Chang, Nobuhiko Mukai
doaj +1 more source