Human activity recognition (HAR) based on wearable sensors is a hot topic in health detection and motion management. Nonetheless, conventional identification methods necessitate substantial labeled datasets, and the acquisition of high-quality labeled data crucial for human activity recognition is both time-consuming and costly. To tackle this problem, transfer learning is used to annotating unlab...Show More
Affective analysis is a technology that aims to understand human sentiment states, and it is widely applied in human–computer interaction and social sentiment analysis. Compared to unimodal, multimodal sentiment analysis (MSA) focuses more on the complementary information and differences from multimodalities, which can better represent the actual sentiment expressed by humans. Existing MSA methods...Show More
The methods based on multimodal representation learning enhance discriminable sentiment expression for multimodal sentiment analysis(MSA). The modal invariant and specific features serve different purposes in sentiment learning and the diversity of inter-sample and inter-category relationships takes less consideration in previous advances. In this paper, we propose a fine-grained tri-modal interac...Show More
Causal inference in the field of infectious disease attempts to gain insight into the potential causal nature of an association between risk factors and diseases. Simulated causality inference experiments have shown preliminary promise in improving understanding of the transmission of infectious diseases but still lack sufficient quantitative causal inference studies based on real-world data. Here...Show More