… In this paper, we propose a novel neural network-based time warping model, called deep
attentive time warping 1 . The proposed method is based on a novel learnable time warping …

… of multivariate time series. In this paper we propose a deep-learning based framework for
clustering multivariate time series data with varying lengths. Our framework, namely DeTSEC (…

… range 14–30 Hz) typically shown in attentive subjects, and intense brain activity or gamma
waves … (for dynamic time warping) and specifying the usage of the SKL metric. A deep LSTM …

… as L2 distance or Dynamic Time Warping based on hand-… of a triplet-based deep metric
learning specifically tailored to … design a novel deep learning architecture based on attentive …

Deep attentive time warping | CiNii Research … Deep attentive time warping … タイトル
Deep attentive time warping …

… intermediate frame at time t \(\in (0,1)\) instantaneously, we adopt a backward warping [17] …
54] to interpolate the frames with estimated flows from time t to 0 and 1, respectively. However, …

… These children have already noticed that time is deeply subjective. Our sense of … that
boredom occurs when ‘we grow attentive to the passage of time itself’. To illustrate this sensation, …

… In this study, we proposed an attentive Bayesian deep learning model that accounts for
long-range spatial dependencies between TZ and PZ with an estimation of pixel-wise uncer…

… Soft Dynamic Time Warping (Soft-DTW) and deep learning, aiming to improve the accuracy
of the system in signature verification tasks. Specifically, we design the attentive time-delay …

… lines of work investigated learning descriptors with deep networks. They generally rely on a
… introduced as an attention mechanism capable of warping the inputs to increase recognition …