Results 11 to 20 of about 523,313 (224)
Time Series Classification with InceptionFCN [PDF]
Sensors, 2021 Deep neural networks (DNN) have proven to be efficient in computer vision and data classification with an increasing number of successful applications. Time series classification (TSC) has been one of the challenging problems in data mining in the last ...
Saidrasul Usmankhujaev +3 more
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Eigen-entropy based time series signatures to support multivariate time series classification [PDF]
Scientific ReportsMost current algorithms for multivariate time series classification tend to overlook the correlations between time series of different variables. In this research, we propose a framework that leverages Eigen-entropy along with a cumulative moving window ...
Abhidnya Patharkar +6 more
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Technology investigation on time series classification and prediction [PDF]
PeerJ Computer Science, 2022 Time series appear in many scientific fields and are an important type of data. The use of time series analysis techniques is an essential means of discovering the knowledge hidden in this type of data.
Yuerong Tong +9 more
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Simulation Study on How Input Data Affects Time-Series Classification Model Results [PDF]
EntropyThis paper discusses the results of a study investigating how input data characteristics affect the performance of time-series classification models. In this experiment, we used 82 synthetically generated time-series datasets, created based on predefined
Maria Sadowska, Krzysztof Gajowniczek
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Adaptive law-based feature representation for time series classification [PDF]
Scientific ReportsTime series classification (TSC) underpins applications across finance, healthcare, and environmental monitoring, yet real-world series often contain noise, local misalignment, and multiscale patterns. We introduce adaptive law-based transformation (ALT),
Marcell T. Kurbucz +4 more
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Deep Temporal Convolution Network for Time Series Classification [PDF]
Sensors, 2021 A neural network that matches with a complex data function is likely to boost the classification performance as it is able to learn the useful aspect of the highly varying data.
Bee Hock David Koh +4 more
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Robust explainer recommendation for time series classification. [PDF]
Data Min Knowl DiscovAbstractTime series classification is a task which deals with temporal sequences, a prevalent data type common in domains such as human activity recognition, sports analytics and general sensing. In this area, interest in explanability has been growing as explanation is key to understand the data and the model better.
Nguyen TT, Le Nguyen T, Ifrim G.
europepmc +4 more sources
Data Augmentation with Suboptimal Warping for Time-Series Classification [PDF]
Sensors, 2019 In this paper, a novel data augmentation method for time-series classification is proposed. In the introduced method, a new time-series is obtained in warped space between suboptimally aligned input examples of different lengths.
Krzysztof Kamycki +2 more
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Time Series Classification with Shapelet and Canonical Features
Applied Sciences, 2022 Shapelet-based time series classification methods are widely adopted models for time series classification tasks. However, the high computational cost greatly limits the practicability of the Shapelet-based methods. What is more, traditional Shapelet can
Hai-Yang Liu +3 more
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Time series classification with random temporal features
Journal of King Saud University: Computer and Information Sciences, 2023 Time series classification exists in widespread domains such as EEG/ECG classification, device anomaly detection, and speaker authentication. Although many methods have been proposed, efficient selection of intuitive temporal features to accurately ...
Cun Ji +6 more
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