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In this paper, we propose an effective, multi-view, multivariate deep classification model for time-series data. Multi-view methods show promise in their ...
Abstract—In this paper, we propose an effective, multi- view, multivariate deep classification model for time-series data. Multi-view methods show promise ...
Nov 2, 2018 · In this paper, we propose an effective, multi-view, multivariate deep classification model for time-series data. Multi-view methods show ...
"Context-Aware Deep Sequence Learning with Multi-View Factor Pooling for Time Series Classification". 2018 IEEE International Conference on Big Data (Big Data) ...
Context-Aware Deep Sequence Learning with Multi-View Factor Pooling for Time Series Classification. S. Bhattacharjee, W. Tolone, M. Elshambakey, I. Cho, ...
在本文中,我们提出了一个有效的、多视图的、多变量的时间序列数据深度分类模型。多视图方法在学习不同独立信息资源之间的相关性和排他性特性方面表现出了潜力。然而,大 ...
In this paper, we propose an effective, multi-view, multivariate deep classification model for time-series data. Multi-view methods show promise in their ...
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(2018) Context-Aware Deep Sequence Learning with Multi-View Factor Pooling for Time Series Classification; ISBN 9781538650356; 2018 IEEE International ...
... Aware Deep Sequence Learning with Multi-View Factor Pooling for Time Series Classification, IEEE Int. Conference in Big Data, Dec 2018; Sreyasee D.B, Junsong ...
Although there exist many types of DNNs, in this review we focus on three main DNN ar- chitectures used for the TSC task: Multi Layer Perceptron (MLP), ...