Nov 24, 2020 · We propose a novel robust temporal feature network (RTFN) for feature extraction in time series classification, containing a temporal feature network (TFN) and ...
The RTFN is responsible for obtaining as many useful representations from the input as possible. The decoder is made up of four fully-connected layers, helping ...
Aug 18, 2020 · We propose a novel robust temporal feature network (RTFN) that contains temporal feature networks and attentional LSTM networks.
Highlights •Propose a robust temporal feature network (RTFN) for feature extraction.•Responsible for capturing local features and relationships among them.
Apr 9, 2021 · This network acts as a relation extraction network to discover the intrinsic relationships among the extracted features at different positions ...
TFN is a residual structure with multiple convolutional layers. It functions as a local-feature extraction network to mine sufficient local features from data.
This work presents a deep contrastive representation learning with self-distillation (DCRLS) for the time series domain and demonstrates that the ...
RTFN: A robust temporal feature network for time series classification. https://doi.org/10.1016/j.ins.2021.04.053 ·. Видання: Information Sciences, 2021, с ...
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RTFN: A robust temporal feature network for time series classification. TimeNet: Pre-trained deep recurrent neural network for time series classification.
Feb 1, 2024 · Zhan, Rtfn: A robust temporal feature network for time series classification, Inf. Sci. 571 (2021) 65–86. Digital Library · Google Scholar. [55].