Results 11 to 20 of about 62,816 (280)
DYNAMIC TIME WARPING FOR CROPS MAPPING [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2020 Dynamic Time Warping (DTW) has been successfully used for crops mapping due to its capability to achieve good classification results when a reduced number of training samples and irregular satellite image time series is available.
M. Belgiu +3 more
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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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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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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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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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Improved Algorithm of Dynamic Time Warping Based on LDTW [PDF]
Jisuanji gongcheng, 2021 Dynamic Time Warping Under Limited Warping Path Length(LDTW) is an algorithm constructed based on the Dynamic Time Warping(DTW) algorithm,and solves the problem of matching points without similarity in DTW,but it tends to be computationally heavy due to ...
XIA Hansong, ZHANG Lisheng, SANG Chunyan
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Similarity join over multiple time series under Dynamic Time Warping
CTU Journal of Innovation and Sustainable Development, 2023 Similarity join over multiple time series is an interesting task of data mining. This task aims at identifying couples of similar subsequences from multiple time series and the two subsequences might have any length and be at any position in the time ...
Bui Cong Giao
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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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shapeDTW: Shape Dynamic Time Warping [PDF]
Pattern Recognition, 2018 Dynamic Time Warping (DTW) is an algorithm to align temporal sequences with possible local non-linear distortions, and has been widely applied to audio, video and graphics data alignments. DTW is essentially a point-to-point matching method under some boundary and temporal consistency constraints. Although DTW obtains a global optimal solution, it does
Zhao, Jiaping, Itti, Laurent
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Dynamic Time Warping under limited warping path length [PDF]
Information Sciences, 2017 Dynamic Time Warping (DTW) is probably the most popular distance measure for time series data, because it captures flexible similarities under time distortions. However, DTW has long been suffering from the pathological alignment problem, and most existing solutions, which essentially impose rigid constraints on the warping path, are likely to miss the
Zhang, Zheng +5 more
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