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IEEE Internet of Things Journal, 2022
The similarity search on sensor data generated by a myriad of sensing devices is a frequently encountered problem in the era of the Internet of Things (IoT).
Haowen Zhang +3 more
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The similarity search on sensor data generated by a myriad of sensing devices is a frequently encountered problem in the era of the Internet of Things (IoT).
Haowen Zhang +3 more
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IEEE Transactions on Instrumentation and Measurement, 2021
Tacho-less order tracking is an effective tool for fault detection in gearboxes operating under speed fluctuations. This technique’s performance depends on extracting instantaneous shaft speed information from a complex multicomponent gearbox signal ...
M. D. Choudhury, Liu Hong, J. Dhupia
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Tacho-less order tracking is an effective tool for fault detection in gearboxes operating under speed fluctuations. This technique’s performance depends on extracting instantaneous shaft speed information from a complex multicomponent gearbox signal ...
M. D. Choudhury, Liu Hong, J. Dhupia
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IEEE Sensors Journal, 2021
This paper proposes a novel 3D action recognition technique that uses time-series information extracted from depth image sequences for use in systems of human daily activity monitoring.
H. Mohammadzade +3 more
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This paper proposes a novel 3D action recognition technique that uses time-series information extracted from depth image sequences for use in systems of human daily activity monitoring.
H. Mohammadzade +3 more
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DYNAMIC POSITIONAL WARPING: DYNAMIC TIME WARPING FOR ONLINE HANDWRITING
International Journal of Pattern Recognition and Artificial Intelligence, 2009This paper addresses the problem of dynamic time warping (DTW) causing unintended matching correspondences when it is employed for online two-dimensional (2D) handwriting signals, and proposes the concept of dynamic positional warping (DPW) in conjunction with DTW for online handwriting matching problems. The proposed DPW allows subsignal translations
WON-DU CHANG, JUNGPIL SHIN
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1984
Two programs are provided, one that generates Ipc and autocorrelation coefficients from the speech utterances and the other that, using dynamic programming, compares the test utterance with the reference utterances and finds the best match. The method used is Constrained Endpoint with 2-to-l range of slope.
Alan Bundy, Lincoln Wallen
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Two programs are provided, one that generates Ipc and autocorrelation coefficients from the speech utterances and the other that, using dynamic programming, compares the test utterance with the reference utterances and finds the best match. The method used is Constrained Endpoint with 2-to-l range of slope.
Alan Bundy, Lincoln Wallen
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Wearable Air-Writing Recognition System employing Dynamic Time Warping
Consumer Communications and Networking Conference, 2021Gesture recognition has been a popular research field under the trend of IoT and intelligent devices. Air-writing is the most challenging and crucial topic in the gesture recognition field.
Y. Luo, Jiang Liu, S. Shimamoto
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Dynamic Time Warping Dissimilarity Matrices
IEEE Potentials, 2018The dynamic time-warping measure (DTW), also known as the DTW distance, is a widely used method that quantifies how dissimilar two time series are from each other. That quantification of the degree of dissimilarity is often motivated by tasks such as data exploration/visualization, clustering, and classification.
Ana Lorena Uribe-Hurtado +2 more
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Dynamic time warping in hardware
Proceedings of the 14th International Conference on Information Integration and Web-based Applications & Services, 2012The Dynamic Time Warping (DTW) algorithm is a commonly used algorithm in matching time sequence data in many applications that require some kind of similarity measure. Though effective, DTW is computationally intensive, and therefore is not suitable for real-time situations. In the past 30 years, there has been some research work on implementing DTW in
Kin Fun Li, James Shueyen Tai
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Geocarto International, 2021
Satellite image time series change detection methods provide comprehensive understanding of land cover changes. Traditional bi-temporal change detection methods in satellite image time series require consistent time series lengths and use only time ...
H. Xing +5 more
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Satellite image time series change detection methods provide comprehensive understanding of land cover changes. Traditional bi-temporal change detection methods in satellite image time series require consistent time series lengths and use only time ...
H. Xing +5 more
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A Time Series Data Augmentation Method Based on Dynamic Time Warping
2021 International Conference on Computer Communication and Artificial Intelligence (CCAI), 2021Deep learning has become a hot research topic in the field of time series analysis and data mining. Training models often requires balanced and large data sets, but on the one hand, the number of different types of data in time series data sets is often ...
Xinyu Yang +3 more
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