Xiangfeng Luo

Emotion Correlation Mining Through Deep Learning Models on Natural Language Text

2020 · IEEE Transactions on Cybernetics

Emotion analysis has been attracting researchers' attention. Most previous works in the artificial-intelligence field focus on recognizing emotion rather than mining the reason why emotions are not or wrongly recognized. The correlation among emotions contributes …

Interdisciplinary knowledge‐based implicit emotion recognition

2020 · Concurrency and Computation Practice and Experience

Summary Detecting different emotions is a key step toward intelligent recommendation and affective computing, which plays an increasingly important role in guiding decisions. There have been a large number of previous work of machine learning …

Multimodal Cross-Attention Bayesian Network for Social News Emotion Recognition

2023

Multimodal emotion recognition comprehensively identifies the emotion contained in multimodal data by bridging the gaps between heterogeneous dataset. In recent years, multimodal emotion recognition methods have gained significant attention and been shown to surpass single-modal …

Efficient Compensation of Action for Reinforcement Learning Policies in Sim2Real

2024

Simulation to reality (sim-to-real) transfer is a promising alternative for training behavioral policies in reinforcement learning (RL). However, many significant differences between the simulator and the real-world environment cause policies to make inconsistent actions in …