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Kar Hoou Hui et al.
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IEEE GEOSCIENCE AND REMOTE SENSING LETTERS (2015)
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Olivier Janssens et al.
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Rolling element bearing diagnostics using the Case Western Reserve University data: A benchmark study
Wade A. Smith et al.
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Biao Leng et al.
NEUROCOMPUTING (2015)
Deep convolutional neural networks for multi-modality isointense infant brain image segmentation
Wenlu Zhang et al.
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ZhiQiang Chen et al.
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L. Gelman et al.
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Van Tung Tran et al.
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Zheng Dou et al.
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A sparse-response deep belief network based on rate distortion theory
Nan-Nan Ji et al.
PATTERN RECOGNITION (2014)
Automatic bearing fault diagnosis based on one-class v-SVM
Diego Fernandez-Francos et al.
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D. H. Pandya et al.
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A new method for expert target recognition system: Genetic wavelet extreme learning machine (GAWELM)
Engin Avci
EXPERT SYSTEMS WITH APPLICATIONS (2013)
Integrating textual analysis and evidential reasoning for decision making in Engineering design
Fiona Browne et al.
KNOWLEDGE-BASED SYSTEMS (2013)
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Jiesi Luo et al.
MEASUREMENT SCIENCE AND TECHNOLOGY (2013)
Adaptive redundant multiwavelet denoising with improved neighboring coefficients for gearbox fault detection
Jinglong Chen et al.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING (2013)
Fault diagnosis of rolling element bearing using cyclic autocorrelation and wavelet transform
P. K. Kankar et al.
NEUROCOMPUTING (2013)
Application and comparison of an ANN-based feature selection method and the genetic algorithm in gearbox fault diagnosis
A. Hajnayeb et al.
EXPERT SYSTEMS WITH APPLICATIONS (2011)
Application of Vibration and Noise Analysis in Water-Lubricated Rubber Bearings Fault Diagnosis
Engao Peng et al.
MECHATRONICS AND MATERIALS PROCESSING I, PTS 1-3 (2011)
Application of nonlinear feature extraction and support vector machines for fault diagnosis of induction motors
Achmad Widodo et al.
EXPERT SYSTEMS WITH APPLICATIONS (2007)
A comparative study of three artificial neural networks for the detection and classification of gear faults
IA Abu-Mahfouz
INTERNATIONAL JOURNAL OF GENERAL SYSTEMS (2005)
Model of MT and MST areas using an autoencoder
K Katayama et al.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS (2003)
Multivariate process monitoring and fault diagnosis by multi-scale PCA
M Misra et al.
COMPUTERS & CHEMICAL ENGINEERING (2002)
Combining belief functions when evidence conflicts
CK Murphy
DECISION SUPPORT SYSTEMS (2000)