Results 11 to 20 of about 3,979,328 (298)
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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Multivariate LSTM-FCNs for time series classification [PDF]
Neural Networks, 2019 Over the past decade, multivariate time series classification has received great attention. We propose transforming the existing univariate time series classification models, the Long Short Term Memory Fully Convolutional Network (LSTM-FCN) and Attention LSTM-FCN (ALSTM-FCN), into a multivariate time series classification model by augmenting the fully ...
Karim, Fazle +3 more
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Deep learning for time series classification: a review [PDF]
Data mining and knowledge discovery, 2019 Time Series Classification (TSC) is an important and challenging problem in data mining. With the increase of time series data availability, hundreds of TSC algorithms have been proposed.
Fawaz, Hassan Ismail +4 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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LSTM Fully Convolutional Networks for Time Series Classification [PDF]
IEEE Access, 2018 Fully convolutional neural networks (FCNs) have been shown to achieve the state-of-the-art performance on the task of classifying time series sequences.
Fazle Karim +3 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