Results 61 to 70 of about 3,979,328 (298)
Adversarial Attacks on Deep Neural Networks for Time Series Classification [PDF]
, 2019 Time Series Classification (TSC) problems are encountered in many real life data mining tasks ranging from medicine and security to human activity recognition and food safety.
Fawaz, Hassan Ismail +4 more
core +1 more source
ShapeNet: A Shapelet-Neural Network Approach for Multivariate Time Series Classification
AAAI Conference on Artificial Intelligence, 2021 Time series shapelets are short discriminative subsequences that recently have been found not only to be accurate but also interpretable for the classification problem of univariate time series (UTS).
Guozhong Li +5 more
semanticscholar +1 more source
LA-ESN: A Novel Method for Time Series Classification
Information, 2023 Time-series data is an appealing study topic in data mining and has a broad range of applications. Many approaches have been employed to handle time series classification (TSC) challenges with promising results, among which deep neural network methods ...
Hui Sheng +5 more
doaj +1 more source
Highly comparative feature-based time-series classification [PDF]
, 2014 A highly comparative, feature-based approach to time series classification is introduced that uses an extensive database of algorithms to extract thousands of interpretable features from time series.
Fulcher, Ben D., Jones, Nick S.
core +1 more source
ShapeFormer: Shapelet Transformer for Multivariate Time Series Classification [PDF]
Knowledge Discovery and Data MiningMultivariate time series classification (MTSC) has attracted significant research attention due to its diverse real-world applications. Recently, exploiting transformers for MTSC has achieved state-of-the-art performance.
Xuan-May Le +3 more
semanticscholar +1 more source
TapNet: Multivariate Time Series Classification with Attentional Prototypical Network
AAAI Conference on Artificial Intelligence, 2020 With the advance of sensor technologies, the Multivariate Time Series classification (MTSC) problem, perhaps one of the most essential problems in the time series data mining domain, has continuously received a significant amount of attention in recent ...
Xuchao Zhang +3 more
semanticscholar +1 more source
A Metric Learning-Based Univariate Time Series Classification Method
Information, 2020 High-dimensional time series classification is a serious problem. A similarity measure based on distance is one of the methods for time series classification.
Kuiyong Song, Nianbin Wang, Hongbin Wang
doaj +1 more source
Imaging time series for the classification of EMI discharge sources [PDF]
, 2018 In this work, we aim to classify a wider range of Electromagnetic Interference (EMI) discharge sources collected from new power plant sites across multiple assets. This engenders a more complex and challenging classification task.
Boreham, Philip +5 more
core +2 more sources
Skewed Time Series Classification Algorithm Based on Persistent Homology [PDF]
Jisuanji gongchengTo address the limitations of traditional time series classification algorithms to extract high-dimensional topological information and temporal sequence information, this paper proposes a skewed time series classification algorithm based on persistent ...
YAN Yinkai, PENG Ningning, YI Lisha
doaj +1 more source
Classification of non‐stationary time series
Stat, 2014 AbstractIn this paper we consider the problem of classifying non‐stationary time series. The method that we introduce is based on the locally stationary wavelet paradigm and seeks to take account of the fact that there may be within‐class variation in the signals being analysed.
Krzemieniewska, Karolina +2 more
openaire +2 more sources