Results 121 to 130 of about 779 (142)
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2020 IEEE Symposium Series on Computational Intelligence (SSCI), 2020
In this work, we introduce the Multichannel Intelligent Icons, a novel method for producing and presenting essential patterns of multidimensional bio-signals. The proposed approach is an extension of Symbolic Aggregate Approximation (SAX) along with an innovative variation of Intelligent Icons.
Lamprini Pappa +3 more
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In this work, we introduce the Multichannel Intelligent Icons, a novel method for producing and presenting essential patterns of multidimensional bio-signals. The proposed approach is an extension of Symbolic Aggregate Approximation (SAX) along with an innovative variation of Intelligent Icons.
Lamprini Pappa +3 more
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Empirical study of symbolic aggregate approximation for time series classification
Intelligent Data Analysis, 2017Symbolic Aggregate approximation (SAX) has been the de facto standard representation methods for knowledge discovery in time series on a number of tasks and applications. So far, very little work has been done in empirically investigating the intrinsic properties and statistical mechanics in SAX words.
Wei Song +4 more
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Genetic Algorithms-Based Symbolic Aggregate Approximation
2012Time series data appear in a broad variety of economic, medical, and scientific applications. Because of their high dimensionality, time series data are managed by using representation methods. Symbolic representation has attracted particular attention because of the possibility it offers to benefit from algorithms and techniques of other fields in ...
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An improved symbolic aggregate approximation distance measure based on its statistical features
Proceedings of the 18th International Conference on Information Integration and Web-based Applications and Services, 2016The challenges in efficient data representation and similarity measures on massive amounts of time series have enormous impact on many applications. This paper addresses an improvement on Symbolic Aggregate approXimation (SAX), is one of the efficient representations for time series mining. Because SAX represents its symbols by the average (mean) value
Chaw Thet Zan, Hayato Yamana
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SAX2SEX: Gender Classification on 3D Faces using Symbolic Aggregate ApproXimation
2019 6th International Conference on Image and Signal Processing and their Applications (ISPA), 2019Gender classification is a demographic attribute that found an increasing amount of applications particularly in human-computer interaction, security access control and biometrics. The purpose of this paper is to investigate the feasibility of using time series for gender classification.
Samia Bentaieb +2 more
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2017 IEEE Symposium on Communications and Vehicular Technology (SCVT), 2017
Radio Frequency (RF) fingerprinting is the problem of identifying and authenticating an electronic device through its radio frequency emissions. These emissions contain intrinsic features of the device itself. RF fingerprinting can be used to enhance the security of wireless networks since the fingerprints provide a form of authentication complementing
Gianmarco Baldini +4 more
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Radio Frequency (RF) fingerprinting is the problem of identifying and authenticating an electronic device through its radio frequency emissions. These emissions contain intrinsic features of the device itself. RF fingerprinting can be used to enhance the security of wireless networks since the fingerprints provide a form of authentication complementing
Gianmarco Baldini +4 more
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2014 13th International Conference on Machine Learning and Applications, 2014
Standard Symbolic Aggregation Approximation (SAX) is at the core of many effective time series data mining algorithms. Its combination with Bag-of-Patterns (BoP) has become the standard approach with state-of-the-art performance on standard datasets. However, standard SAX with the BoP representation might neglect internal temporal correlation embedded ...
Zhiguang Wang, Tim Oates 0001
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Standard Symbolic Aggregation Approximation (SAX) is at the core of many effective time series data mining algorithms. Its combination with Bag-of-Patterns (BoP) has become the standard approach with state-of-the-art performance on standard datasets. However, standard SAX with the BoP representation might neglect internal temporal correlation embedded ...
Zhiguang Wang, Tim Oates 0001
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Dynamic Biometric Recognition of Handwritten Digits Using Symbolic Aggregate Approximation
Proceedings of the SouthEast Conference, 2017Symbolic aggregate approximation (SAX) is an ideal technique for dynamic biometric recognition of handwritten digits. The manipulation of time series in SAX readily lends itself to analysis of the spatial coordinate data acquired from a digit written on the touchscreen of a smartphone or tablet. SAX generates a sequence of alphabetic characters derived
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Gesture recognition using symbolic aggregate approximation and dynamic time warping on motion data
Proceedings of the 11th EAI International Conference on Pervasive Computing Technologies for Healthcare, 2017In the area of advanced human-computer interaction, automatic gesture recognition is an important field. Motion data produced by the accelerometer of a smart watch can be utilized in hand gesture recognition. In this work we examine the use of a commodity smart watch and a smartphone as the capture and the processing units respectively, for recognizing
Antigoni Mezari, Ilias Maglogiannis
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