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[PDF] Top 20 Feature Extraction and Selection in Automatic Sleep Stage Classification

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Feature Extraction and Selection in Automatic Sleep Stage Classification

Feature Extraction and Selection in Automatic Sleep Stage Classification

... a feature selection method was proposed in this ...of feature vectors is calculated, then considering the range of the extracted L1-norm, a similarity threshold is ...The feature pair ... See full document

177

Classifier ensemble feature selection for automatic fault diagnosis

Classifier ensemble feature selection for automatic fault diagnosis

... used in the fault diagnosis context presenting good results, commonly compatibles or superior than more sophisticated algorithms as Support Vector Machine (SVM), Adaboost and Random Forests ( ... See full document

112

Comparative analysis of strategies for feature extraction and classification in SSVEP BCIs.

Comparative analysis of strategies for feature extraction and classification in SSVEP BCIs.

... for feature extraction and incremental wrappers to carry out feature ...The feature extraction tech- niques showed to be equivalent to estimate the spectral ...Welch and ... See full document

9

Automatic quantification and classification of breast density in 2D ultrasound images

Automatic quantification and classification of breast density in 2D ultrasound images

... density and the risk of breast ...fat in the breast ...[15-39], and only a few methods consider ultrasound ...processing and its steps: image acquisition, image processing, segmentation, ... See full document

105

Feature Extraction based Face Recognition, Gender and Age Classification

Feature Extraction based Face Recognition, Gender and Age Classification

... Moghaddam and Ming-Hsuan [16] developed an appearance based method to classify gender from facial images using nonlinear SVMs and compared their performance with traditional classifiers and modern ... See full document

10

UNLABELED SELECTED SAMPLES IN FEATURE EXTRACTION FOR CLASSIFICATION OF HYPERSPECTRAL IMAGES WITH LIMITED TRAINING SAMPLES

UNLABELED SELECTED SAMPLES IN FEATURE EXTRACTION FOR CLASSIFICATION OF HYPERSPECTRAL IMAGES WITH LIMITED TRAINING SAMPLES

... increased in number. For IP dataset, maximum average accuracy in ill-posed classification problem with GML classifier using LPPURS and SSMFAURS features are ...accuracy in the same ... See full document

6

Study of Automatic Extraction, Classification, and Ranking of Product Aspects Based on Sentiment Analysis of Reviews

Study of Automatic Extraction, Classification, and Ranking of Product Aspects Based on Sentiment Analysis of Reviews

... reflect and distribute the effect of some negative words to its surrounding opinion ...text classification problem, but a particular linguistic feature ...challenges and problems to these ... See full document

6

Investigating the contribution of distance-based features to automatic sleep stage classification

Investigating the contribution of distance-based features to automatic sleep stage classification

... the sleep scoring system. This improvement is noticeable in the results of all three ...total feature set are sufficient to reach, on average, 85% accuracy, and usually 612 ... See full document

39

Higher order feature extraction and selection for robust human gesture recognition using CSI of COTS Wi-Fi devices

Higher order feature extraction and selection for robust human gesture recognition using CSI of COTS Wi-Fi devices

... for feature extraction and selection, as it has a high impact on recognition accuracy of learning ...popular feature extraction technique to extract the principal components from ... See full document

23

Feature extraction and selection analysis in biological sequence: a case study with metaheuristics and mathematical models

Feature extraction and selection analysis in biological sequence: a case study with metaheuristics and mathematical models

... for feature extraction in order to propose efficient and generalist techniques for biological sequence analysis ...this stage, as a starting point, nine mathematical models for ... See full document

105

Image Processing Techniques for Denoising, Object Identification and Feature Extraction

Image Processing Techniques for Denoising, Object Identification and Feature Extraction

... first stage involves the initial estimation of the image by removing much of the noise and the second stage involves the further refinement of the first ...first and second stage ... See full document

6

Sequence-based classification using discriminatory motif feature selection.

Sequence-based classification using discriminatory motif feature selection.

... interest in linking sequence information to biological ...haplotypes). In many other settings, however, this is not the case and the direct analysis of sequence data may not be ...sequence-based ... See full document

7

Sleep Stage Classification: A Deep Learning Approach

Sleep Stage Classification: A Deep Learning Approach

... etc.) and generative/unsupervised models ...generative and discriminative model components. This two-way classification scheme, however, misses a key insight gained in deep learning research ... See full document

187

Automatic extraction of definitions

Automatic extraction of definitions

... obtained in the grammar was carried out (Westerhout & Monachesi, ...the selection of ...bigrams, and bigram preceding the definition), syntactic properties (type of determiner within the defined ... See full document

205

Feature extraction and selection for automatic hate speech detection on Twitter

Feature extraction and selection for automatic hate speech detection on Twitter

... of automatic hate speech detection in text was poorly addressed up until mid-2017 and 2018, and the existing approaches were not so popular, with the number of citations averag- ing around ... See full document

109

Automatic analysis of skin lesions in dermoscopy images: feature extraction and classification

Automatic analysis of skin lesions in dermoscopy images: feature extraction and classification

... and the surrounding skin. With few exceptions, these measures figured in the top rankings of all three methods, for both datasets, which suggests that these features should be the most reliable for ... See full document

125

Morphological feature selection and neural classification

Morphological feature selection and neural classification

... processing and feature extraction. The open-source and Java-based application ImageJ was used as a platform for this task ...scaled and cropped, and the colour infor- mation was ... See full document

6

Selecting Features of Single Lead ECG Signal for Automatic Sleep Stages Classification using Correlation-based Feature Subset Selection

Selecting Features of Single Lead ECG Signal for Automatic Sleep Stages Classification using Correlation-based Feature Subset Selection

... our sleep quality will help human life to maximize our life ...the sleep stages so that sleep quality can be ...used in this research is single lead ECG signal from the MIT-BIH ... See full document

10

Automated Feature Engineering for Classification Problems

Automated Feature Engineering for Classification Problems

... Automated Feature Engineering has two approaches to feature extraction, called expand-reduce and ...for feature engineer- ing as we can see the Deep Feature Synthesis [6], ... See full document

64

Diversity in automatic cloud computing resource selection

Diversity in automatic cloud computing resource selection

... an automatic diversity management component, we found basically two automatic diversity management ...bility and bugs independence through OS ...resource selection scenario, where, even both ... See full document

91

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