most citedConcurrent Activity Recognition with Multimodal CNN-LSTM Structure

32 citations · 32 across the 2 of their papers we have counts for

collaborators

5 papers

cs.CV2018

Tri-axial Self-Attention for Concurrent Activity Recognition

Yanyi Zhang, Xinyu Li, Kaixiang Huang +3

We present a system for concurrent activity recognition. To extract features associated with different activities, we propose a feature-to-activity attention that maps the extracte…

cs.CL2018

Multimodal Affective Analysis Using Hierarchical Attention Strategy with Word-Level Alignment

Yue Gu, Kangning Yang, Shiyu Fu +3

Multimodal affective computing, learning to recognize and interpret human affects and subjective information from multiple data sources, is still challenging because: (i) it is har…

cs.CL2018

Deep Multimodal Learning for Emotion Recognition in Spoken Language

Yue Gu, Shuhong Chen, Ivan Marsic

In this paper, we present a novel deep multimodal framework to predict human emotions based on sentence-level spoken language. Our architecture has two distinctive characteristics.…

cs.DS2017

Process-oriented Iterative Multiple Alignment for Medical Process Mining

Shuhong Chen, Sen Yang, Moliang Zhou +2

Adapted from biological sequence alignment, trace alignment is a process mining technique used to visualize and analyze workflow data. Any analysis done with this method, however,…

cs.CV201732 cited

Concurrent Activity Recognition with Multimodal CNN-LSTM Structure

Xinyu Li, Yanyi Zhang, Jianyu Zhang +4

We introduce a system that recognizes concurrent activities from real-world data captured by multiple sensors of different types. The recognition is achieved in two steps. First, w…