Insights Into LSTM Fully Convolutional Networks for Time Series Classification

Volume: 7, Pages: 67718 - 67725
Published: May 14, 2019
Abstract
Long short-term memory fully convolutional neural networks (LSTM-FCNs) and Attention LSTM-FCN (ALSTM-FCN) have shown to achieve the state-of-the-art performance on the task of classifying time series signals on the old University of California-Riverside (UCR) time series repository. However, there has been no study on why LSTM-FCN and ALSTM-FCN perform well. In this paper, we perform a series of ablation tests (3627 experiments) on the LSTM-FCN...
Paper Details
Title
Insights Into LSTM Fully Convolutional Networks for Time Series Classification
Published Date
May 14, 2019
Volume
7
Pages
67718 - 67725
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