Results 11 to 20 of about 59,702 (203)
Efficient search of the best warping window for Dynamic Time Warping [PDF]
Time series classification maps time series to labels. The nearest neighbor algorithm (NN) using the Dynamic Time Warping (DTW) similarity measure is a leading algorithm for this task and a component of the current best ensemble classifiers for time series.
Chang Wei Tan+4 more
openalex +2 more sources
Similarity join over multiple time series under Dynamic Time Warping
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
doaj +3 more sources
Tight lower bounds for dynamic time warping [PDF]
26 pages, 23 figures, expanded version of a paper accepted for publication in Pattern Recognition.
François Petitjean, Geoffrey I. Webb
openaire +3 more sources
Efficient Time Series Clustering by Minimizing Dynamic Time Warping Utilization
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
doaj +1 more source
Improved LDTW Algorithm Based on the Alternating Matrix and the Evolutionary Chain Tree
Dynamic time warping under limited warping path length (LDTW) is a state-of-the-art time series similarity evaluation method. However, it suffers from high space-time complexity, which makes some large-scale series evaluations impossible.
Zheng Zou+3 more
doaj +1 more source
Seeded Classification of Satellite Image Time Series with Lower-Bounded Dynamic Time Warping
Satellite Image Time Series (SITS) record the continuous temporal behavior of land cover types and thus provide a new perspective for finer-grained land cover classification compared with the usual spectral and spatial information contained in a static ...
Zheng Zhang+5 more
doaj +1 more source
Voice Transformation Using Two-Level Dynamic Warping and Neural Networks
Voice transformation, for example, from a male speaker to a female speaker, is achieved here using a two-level dynamic warping algorithm in conjunction with an artificial neural network.
Al-Waled Al-Dulaimi+2 more
doaj +1 more source
Learning Discriminative Prototypes with Dynamic Time Warping [PDF]
Dynamic Time Warping (DTW) is widely used for temporal data processing. However, existing methods can neither learn the discriminative prototypes of different classes nor exploit such prototypes for further analysis. We propose Discriminative Prototype DTW (DP-DTW), a novel method to learn class-specific discriminative prototypes for temporal ...
Xiaobin Chang, Frederick Tung, Greg Mori
openaire +3 more sources
Pairwise dynamic time warping for event data [PDF]
We introduce a new version of dynamic time warping for samples of observed event times that are modeled as time-warped intensity processes. Our approach is devel- oped within a framework where for each experimental unit or subject in a sample, one observes a random number of event times or random locations.
Ana Arribas-Gil, Hans-Georg Müller
openaire +3 more sources
IDENTIFIKASI WAJAH MENGGUNAKAN KLASIFIKASI DYNAMIC TIME WARPING
Di era modern saat ini, banyak organisasi-organisasi, institusi maupun perusahaan yang membutuhkan adanya identifikasi dan verifikasi akan identitas seseorang.
Febri Ariyanto
doaj +1 more source