Trear: Transformer-based rgb-d egocentric action recognition
In this article, we propose a transformer-based RGB-D egocentric action recognition
framework, called Trear. It consists of two modules: 1) interframe attention encoder and 2) …
framework, called Trear. It consists of two modules: 1) interframe attention encoder and 2) …
Adaptive spatiotemporal representation learning for skeleton-based human action recognition
How do humans recognize an action or an interaction in the real world? Due to the diversity
of viewing perspectives, it is a challenge for humans to identify a regular activity when they …
of viewing perspectives, it is a challenge for humans to identify a regular activity when they …
Deep echo state network with multiple adaptive reservoirs for time series prediction
Z Wang, X Yao, Z Huang, L Liu - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
In this article, considering the plasticity of reservoir, a deep echo state network with multiple
adaptive reservoirs in series configuration, called MAR-DESN, is proposed for time series …
adaptive reservoirs in series configuration, called MAR-DESN, is proposed for time series …
A circadian rhythms learning network for resisting cognitive periodic noises of time-varying dynamic system and applications to robots
Time-varying dynamic system contaminated by cognitive noises is universal in the fields of
engineering and science. In this article, a circadian rhythms learning network (CRLN) is …
engineering and science. In this article, a circadian rhythms learning network (CRLN) is …
Attention-based parallel multiscale convolutional neural network for visual evoked potentials EEG classification
Z Gao, X Sun, M Liu, W Dang, C Ma… - IEEE Journal of …, 2021 - ieeexplore.ieee.org
Electroencephalography (EEG) decoding is an important part of Visual Evoked Potentials-
based Brain-Computer Interfaces (BCIs), which directly determines the performance of BCIs …
based Brain-Computer Interfaces (BCIs), which directly determines the performance of BCIs …
Adaptive backstepping terminal sliding mode control of nonlinear system using fuzzy neural structure
X Gong, W Fu, X Bian, J Fei - Mathematics, 2023 - mdpi.com
An adaptive backstepping terminal sliding mode control (ABTSMC) method based on a
multiple− layer fuzzy neural network is proposed for a class of nonlinear systems with …
multiple− layer fuzzy neural network is proposed for a class of nonlinear systems with …
Adaptive detrending to accelerate convolutional gated recurrent unit training for contextual video recognition
Video image recognition has been extensively studied with rapid progress recently.
However, most methods focus on short-term rather than long-term (contextual) video …
However, most methods focus on short-term rather than long-term (contextual) video …
Adaptive graph convolutional network with adversarial learning for skeleton-based action prediction
G Li, N Li, F Chang, C Liu - IEEE Transactions on Cognitive …, 2021 - ieeexplore.ieee.org
The purpose of action prediction is to recognize an action before it is completed to reduce
recognition latency. Because action prediction has lower latency than action recognition, it …
recognition latency. Because action prediction has lower latency than action recognition, it …
Multi-agent transformer networks for multimodal human activity recognition
Human activity recognition has become an important challenge yet to resolve while also
having promising benefits in various applications for years. Existing approaches have made …
having promising benefits in various applications for years. Existing approaches have made …
Distilled mid-fusion transformer networks for multi-modal human activity recognition
Human Activity Recognition is an important task in many human-computer collaborative
scenarios, whilst having various practical applications. Although uni-modal approaches …
scenarios, whilst having various practical applications. Although uni-modal approaches …