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Adaptively constrained dynamic time war** for time series classification and clustering
Time series classification and clustering are important for data mining research, which is
conducive to recognizing movement patterns, finding customary routes, and detecting …
conducive to recognizing movement patterns, finding customary routes, and detecting …
A transfer Learning-Based LSTM strategy for imputing Large-Scale consecutive missing data and its application in a water quality prediction system
Z Chen, H Xu, P Jiang, S Yu, G Lin, I Bychkov… - Journal of …, 2021 - Elsevier
In recent years, water quality monitoring has been crucial to improve water resource
protection and management. Under the relevant laws and regulations, environmental …
protection and management. Under the relevant laws and regulations, environmental …
Interpretable heartbeat classification using local model-agnostic explanations on ECGs
Abstract Treatment and prevention of cardiovascular diseases often rely on
Electrocardiogram (ECG) interpretation. Dependent on the physician's variability, ECG …
Electrocardiogram (ECG) interpretation. Dependent on the physician's variability, ECG …
Time-series averaging and local stability-weighted dynamic time war** for online signature verification
M Okawa - Pattern Recognition, 2021 - Elsevier
To meet the recent demands for automated security systems, this study proposes a novel
single-template strategy that uses mean templates and local stability-weighted dynamic time …
single-template strategy that uses mean templates and local stability-weighted dynamic time …
Soft contrastive learning for time series
S Lee, T Park, K Lee - ar** to improve time series classification
Y Liu, YA Zhang, M Zeng, J Zhao - Information Sciences, 2024 - Elsevier
Dynamic time war** (DTW) is the most widely used method to evaluate the similarity
between time series. However, the DTW distance only takes into account the difference in …
between time series. However, the DTW distance only takes into account the difference in …
[HTML][HTML] Tssearch: Time series subsequence search library
Subsequence search and distance measures are crucial tools in time series data mining.
This paper presents our Python package entitled TSSEARCH, which provides a …
This paper presents our Python package entitled TSSEARCH, which provides a …
BioTouchPass2: Touchscreen password biometrics using time-aligned recurrent neural networks
Passwords are still used on a daily basis for all kind of applications. However, they are not
secure enough by themselves in many cases. This work enhances password scenarios …
secure enough by themselves in many cases. This work enhances password scenarios …
Real-time fire detection system based on dynamic time war** of multichannel sensor networks
Fires are considered one of the most devastating accidents that could occur within a
building. However, existing fire detection systems result in late fire detection or produce a …
building. However, existing fire detection systems result in late fire detection or produce a …
[HTML][HTML] Within-day travel speed pattern unsupervised classification–A data driven case study of the State of Alabama during the COVID-19 pandemic
Recent comparative studies on mobility patterns are emerging to describe the changes in
mobility patterns due to the COVID-19 pandemic. Most of the current studies utilize travel …
mobility patterns due to the COVID-19 pandemic. Most of the current studies utilize travel …