Using Multi-Dimensional Dynamic Time Warping to Identify Time-Varying Lead-Lag Relationships [PDF]
Sensors, 2022 This paper develops a multi-dimensional Dynamic Time Warping (DTW) algorithm to identify varying lead-lag relationships between two different time series.
Johannes Stübinger, Dominik Walter
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Development of Smart Healthcare System Based on Speech Recognition Using Support Vector Machine and Dynamic Time Warping [PDF]
Sustainability, 2020 This paper presents an effective solution based on speech recognition to provide elderly people, patients and disabled people with an easy control system.
Ahmed Ismail +2 more
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Efficient Time Series Clustering by Minimizing Dynamic Time Warping Utilization
IEEE Access, 2021 Dynamic Time Warping (DTW) is a widely used distance measurement in time series clustering. DTW distance is invariant to time series phase perturbations but has a quadratic complexity.
Borui Cai +4 more
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Malaysia PM10 Air Quality Time Series Clustering Based on Dynamic Time Warping
Atmosphere, 2022 Air quality monitoring is important in the management of the environment and pollution. In this study, time series of PM10 from air quality monitoring stations in Malaysia were clustered based on similarity in terms of time series patterns.
Fatin Nur Afiqah Suris +4 more
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Dynamic Time Warping as a Means of Assessing Solar Wind Time Series [PDF]
Astrophysical Journal, 2022 Over the last decades, international attempts have been made to develop realistic space weather prediction tools aiming to forecast the conditions on the Sun and in the interplanetary environment.
Evangelia Samara +7 more
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Feature trajectory dynamic time warping for clustering of speech segments [PDF]
EURASIP Journal on Audio, Speech, and Music Processing, 2019 Dynamic time warping (DTW) can be used to compute the similarity between two sequences of generally differing length. We propose a modification to DTW that performs individual and independent pairwise alignment of feature trajectories.
Lerato Lerato, Thomas Niesler
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Weakly Supervised Temporal Anomaly Segmentation with Dynamic Time Warping [PDF]
IEEE International Conference on Computer Vision, 2021 Most recent studies on detecting and localizing temporal anomalies have mainly employed deep neural networks to learn the normal patterns of temporal data in an unsupervised manner. Unlike them, the goal of our work is to fully utilize instance-level (or
Dongha Lee +3 more
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Computing and Visualizing Dynamic Time Warping Alignments in R: The dtw Package [PDF]
Journal of Statistical Software, 2009 Dynamic time warping is a popular technique for comparing time series, providing both a distance measure that is insensitive to local compression and stretches and the warping which optimally deforms one of the two input series onto the other.
Toni Giorgino
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Head Gesture Recognition Combining Activity Detection and Dynamic Time Warping [PDF]
Journal of ImagingThe recognition of head movements plays an important role in human–computer interface domains. The data collected with image sensors or inertial measurement unit (IMU) sensors are often used for identifying these types of actions.
Huaizhou Li, Haiyan Hu
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Object-Based Time-Constrained Dynamic Time Warping Classification of Crops Using Sentinel-2
Remote Sensing, 2019 The increasing volume of remote sensing data with improved spatial and temporal resolutions generates unique opportunities for monitoring and mapping of crops.
Ovidiu Csillik +3 more
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