Parallel spatio-temporal attention-based TCN for multivariate time series prediction
J Fan, K Zhang, Y Huang, Y Zhu, B Chen - Neural Computing and …, 2023 - Springer
As industrial systems become more complex and monitoring sensors for everything from
surveillance to our health become more ubiquitous, multivariate time series prediction is …
surveillance to our health become more ubiquitous, multivariate time series prediction is …
Asformer: Transformer for action segmentation
Algorithms for the action segmentation task typically use temporal models to predict what
action is occurring at each frame for a minute-long daily activity. Recent studies have shown …
action is occurring at each frame for a minute-long daily activity. Recent studies have shown …
Ms-tct: Multi-scale temporal convtransformer for action detection
Action detection is an essential and challenging task, especially for densely labelled
datasets of untrimmed videos. The temporal relation is complex in those datasets, including …
datasets of untrimmed videos. The temporal relation is complex in those datasets, including …
Learning an augmented rgb representation with cross-modal knowledge distillation for action detection
In video understanding, most cross-modal knowledge distillation (KD) methods are tailored
for classification tasks, focusing on the discriminative representation of the trimmed videos …
for classification tasks, focusing on the discriminative representation of the trimmed videos …
Pdan: Pyramid dilated attention network for action detection
Handling long and complex temporal information is an important factor for action detection
tasks. This challenge is further aggravated by densely distributed actions in untrimmed …
tasks. This challenge is further aggravated by densely distributed actions in untrimmed …
Two birds with one stone: Knowledge-embedded temporal convolutional transformer for depression detection and emotion recognition
W Zheng, L Yan, FY Wang - IEEE Transactions on Affective …, 2023 - ieeexplore.ieee.org
Depression is a critical problem in modern society that affects an estimated 350 million
people worldwide, causing feelings of sadness and a lack of interest and pleasure …
people worldwide, causing feelings of sadness and a lack of interest and pleasure …
Pay attention to doctor–patient dialogues: Multi-modal knowledge graph attention image-text embedding for COVID-19 diagnosis
W Zheng, L Yan, C Gou, ZC Zhang, JJ Zhang, M Hu… - Information …, 2021 - Elsevier
The sudden increase in coronavirus disease 2019 (COVID-19) cases puts high pressure on
healthcare services worldwide. At this stage, fast, accurate, and early clinical assessment of …
healthcare services worldwide. At this stage, fast, accurate, and early clinical assessment of …
Self-attention transfer networks for speech emotion recognition
Background A crucial element of human–machine interaction, the automatic detection of
emotional states from human speech has long been regarded as a challenging task for …
emotional states from human speech has long been regarded as a challenging task for …
Opitrack: a wearable-based clinical opioid use tracker with temporal convolutional attention networks
Opioid use disorder is a medical condition with major social and economic consequences.
While ubiquitous physiological sensing technologies have been widely adopted and …
While ubiquitous physiological sensing technologies have been widely adopted and …
Ctrn: Class-temporal relational network for action detection
Action detection is an essential and challenging task, especially for densely labelled
datasets of untrimmed videos. There are many real-world challenges in those datasets, such …
datasets of untrimmed videos. There are many real-world challenges in those datasets, such …