全部文献期刊会议图书|学者科研项目
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作者:Zhonghua Liu , Zhihui Lai , Weihua Ou ...
来源:[J].Signal Processing(IF 1.851), 2020, Vol.170
摘要:Abstract(#br)Graph-based feature extraction is an efficient technique for data dimensionality reduction, and it has gained intensive attention in various fields such as image processing, pattern recognition, and machine learning. However, conventional graph-based dimensionality r...
作者:Wuhong Lin , Jianfeng Huang , Ching Yee Suen ...
来源:[J].Expert Systems With Applications(IF 1.854), 2020, Vol.139
摘要:... Feature extraction is a key step for classifier learning. However, the relation among samples is usually ignored in classical feature extraction models. Recently, feature extraction based on graph signal processing that makes use of the relation among samples has attracted gr...
作者:Jinxin Zhang , Peng Zhang , Liming Liu ...
来源:[J].Engineering Applications of Artificial Intelligence(IF 1.625), 2020, Vol.90
摘要:Abstract(#br)Most of the current multi-view feature extraction methods mainly consider the consistency and complementary information between multi-view samples, therefore have some drawbacks. They ignore the manifold structure of the single-view itself, and also ignore the differ...
作者:Sridhar Krishnan , Yashodhan Athavale
来源:[J].Biomedical Signal Processing and Control(IF 1.074), 2018, Vol.43, pp.41-63
摘要:... The intention behind this is simple – robust and efficient feature extraction; i.e. to identify specific signal markers or properties exhibited in one event, and use them to distinguish from characteristics exhibited in another event. The objective of our study is to give...
作者:Sreenivas Sremath Tirumala , Seyed Reza Shahamiri , Abhimanyu Singh Garhwal ...
来源:[J].Expert Systems With Applications(IF 1.854), 2017, Vol.90, pp.250-271
摘要:... Feature extraction is one of the most important aspects of SI, which significantly influences the SI process and performance. This systematic review is conducted to identify, compare, and analyze various feature extraction approaches, methods, and algorithms of SI to provide ...
作者:Kaplan Kaplan , Yılmaz Kaya , Melih Kuncan ...
来源:[J].Applied Soft Computing Journal(IF 2.14), 2020, Vol.87
摘要:... The feature extraction process is an essential part of fault diagnosis in bearings. In order to diagnose the fault caused by the bearing correctly, it is necessary to determine an effective feature extraction method that best describes the fault.(#br)In this study, a new appr...
作者:Sebastian Pölsterl , Sailesh Conjeti , Nassir Navab ...
来源:[J].Artificial Intelligence In Medicine(IF 1.355), 2016, Vol.72, pp.1-11
摘要:... Its application to electronic health records is challenging for two main reasons: (1) patient records are comprised of high-dimensional feature vectors, and (2) feature vectors are a mix of categorical and real-valued features, which implies varying statistical propertie...
作者:Jianquan Shi , Gangquan Si , Shuiwang Li ...
来源:[J].Control Engineering Practice(IF 1.669), 2019, Vol.84, pp.238-246
摘要:Abstract(#br)Feature extraction plays a major role in data preprocessing and soft sensing. In this paper, a feature extraction method based on the fractional Fourier transform (FrFT) is proposed to estimate the load of a tubular ball mill. The FrFT, a generalised form of FFT,...
作者:Zheng-Yong Zhang , Dong-Dong Gui , Min Sha ...
来源:[J].Journal of Dairy Science(IF 2.566), 2019, Vol.102 (1), pp.68-76
摘要:... Feature extraction is a necessary processing step to improve the efficiency of Raman spectral data. Principal component analysis is a traditional method that can effectively extract the features and reduce the dimension of spectral data. However, it is difficult to analyze th...
作者:Ruqayya Awan , Kashif Rajpoot
来源:[J].Computers in Biology and Medicine(IF 1.162), 2015, Vol.64, pp.138-147
摘要:Abstract(#br)Background(#br)Ultrasound images are difficult to segment because of their noisy and low contrast nature which makes it challenging to extract the important features. Typical intensity-gradient based approaches are not suitable for these low contrast images while it ...

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