A review of unsupervised feature learning and deep learning for time-series modeling
This paper gives a review of the recent developments in deep learning and unsupervised
feature learning for time-series problems. While these techniques have shown promise for …
feature learning for time-series problems. While these techniques have shown promise for …
Unsupervised fault diagnosis of rolling bearings using a deep neural network based on generative adversarial networks
H Liu, J Zhou, Y Xu, Y Zheng, X Peng, W Jiang - Neurocomputing, 2018 - Elsevier
Fault diagnosis of rolling bearing has been research focus to improve the productivity and
guarantee the operation security. In general, traditional approaches need prior knowledge of …
guarantee the operation security. In general, traditional approaches need prior knowledge of …
Generalized time warping for multi-modal alignment of human motion
F Zhou, F De la Torre - 2012 IEEE Conference on Computer …, 2012 - ieeexplore.ieee.org
Temporal alignment of human motion has been a topic of recent interest due to its
applications in animation, telerehabilitation and activity recognition among others. This …
applications in animation, telerehabilitation and activity recognition among others. This …
Generalized canonical time warping
F Zhou, F De la Torre - IEEE transactions on pattern analysis …, 2015 - ieeexplore.ieee.org
Temporal alignment of human motion has been of recent interest due to its applications in
animation, tele-rehabilitation and activity recognition. This paper presents generalized …
animation, tele-rehabilitation and activity recognition. This paper presents generalized …
Modeling dynamical influence in human interaction: Using data to make better inferences about influence within social systems
How can we model influence between individuals in a social system, even when the network
of interactions is unknown? In this article, we review the literature on the “influence model,” …
of interactions is unknown? In this article, we review the literature on the “influence model,” …
[HTML][HTML] Unsupervised fault diagnosis of a gear transmission chain using a deep belief network
J He, S Yang, C Gan - Sensors, 2017 - mdpi.com
Artificial intelligence (AI) techniques, which can effectively analyze massive amounts of fault
data and automatically provide accurate diagnosis results, have been widely applied to fault …
data and automatically provide accurate diagnosis results, have been widely applied to fault …
Geppetto: Enabling semantic design of expressive robot behaviors
Expressive robots are useful in many contexts, from industrial to entertainment applications.
However, designing expressive robot behaviors requires editing a large number of …
However, designing expressive robot behaviors requires editing a large number of …
Society's nervous system: Building effective government, energy, and public health systems
AS Pentland - Computer, 2011 - ieeexplore.ieee.org
Society's Nervous System: Page 1 To Appear: IEEE Computer OUTLOOK Issue, January 2012
Society's Nervous System: Building Effective Government, Energy, and Public Health Systems …
Society's Nervous System: Building Effective Government, Energy, and Public Health Systems …
Movement extraction by detecting dynamics switches and repetitions
Many time-series such as human movement data consist of a sequence of basic actions, eg,
forehands and backhands in tennis. Automatically extracting and characterizing such …
forehands and backhands in tennis. Automatically extracting and characterizing such …
Human activity prediction using temporally-weighted generalized time warping
Different from traditional human activity recognition, human activity prediction aims to
recognize an unfinished activity, typically in absence of explicit temporal progress status. In …
recognize an unfinished activity, typically in absence of explicit temporal progress status. In …