Journal ArticleDOI
Multi-scale signed recurrence plot based time series classification using inception architectural networks
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This article is published in Pattern Recognition.The article was published on 2022-03-01. It has received 15 citations till now. The article focuses on the topics: Computer science & Scale (ratio).read more
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Journal ArticleDOI
Multi-scale and multi-layer perceptron hybrid method for bearings fault diagnosis
TL;DR: In this article , a multi-scale multi-layer perceptron (MSMLP) hybrid bearing fault diagnosis based on complementary ensemble empirical mode decomposition (CEEMD) is proposed, inspired by the successful application of deep networks in the field of computer vision.
Journal ArticleDOI
Discriminative and regularized echo state network for time series classification
TL;DR: In this article , a novel discriminative and regularized echo state network (DR-ESN) is proposed for time series classification, which combines feature aggregation (DFA) and outlier robust weights (ORW) algorithms.
Proceedings ArticleDOI
Spike2Signal: Classifying Coronavirus Spike Sequences with Deep Learning
TL;DR: Spike2Signal as mentioned in this paper converts spike sequences into a signal-like representation to allow the classification by state-of-the-art time-series classifiers, and transforms this Spike2signal representation into an image to enable the usage of state of the art image classifiers.
Journal ArticleDOI
Knowledge transfer via distillation from time and frequency domain for time series classification
Journal ArticleDOI
Noise-robust machinery fault diagnosis based on self-attention mechanism in wavelet domain
TL;DR: Wang et al. as discussed by the authors proposed an anti-noise wavelet based self-attention network for machinery fault diagnosis, named Wavelet-SANet, which combines the frequency-oriented fusion modules and the Transformer modules to restrain noise in both frequency and time domains.
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Posted Content
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift
Sergey Ioffe,Christian Szegedy +1 more
TL;DR: Batch Normalization as mentioned in this paper normalizes layer inputs for each training mini-batch to reduce the internal covariate shift in deep neural networks, and achieves state-of-the-art performance on ImageNet.
Journal Article
Statistical Comparisons of Classifiers over Multiple Data Sets
TL;DR: A set of simple, yet safe and robust non-parametric tests for statistical comparisons of classifiers is recommended: the Wilcoxon signed ranks test for comparison of two classifiers and the Friedman test with the corresponding post-hoc tests for comparisons of more classifiers over multiple data sets.
Journal ArticleDOI
Recurrence plots for the analysis of complex systems
TL;DR: The aim of this work is to provide the readers with the know how for the application of recurrence plot based methods in their own field of research, and detail the analysis of data and indicate possible difficulties and pitfalls.
Journal ArticleDOI
Recurrence Plots of Dynamical Systems
TL;DR: In this article, a graphical tool for measuring the time constancy of dynamical systems is presented and illustrated with typical examples, and the tool can be used to measure the time complexity of a dynamical system.
Journal ArticleDOI
Data mining with big data
TL;DR: A HACE theorem is presented that characterizes the features of the Big Data revolution, and a Big Data processing model is proposed, from the data mining perspective, which involves demand-driven aggregation of information sources, mining and analysis, user interest modeling, and security and privacy considerations.