LineConvGraphs: Line Conversation Graphs for Effective Emotion Recognition Using Graph Neural Networks

A New Approach to Emotion Recognition in Conversations Based on Graph Neural Networks Research Background Emotion recognition (ER) is an important component of human-computer interaction (HCI), aiming to identify human emotional states by analyzing multimodal data such as speech, text, and video. This technology has broad application prospects in f...

CSE-GResNet: A Simple and Highly Efficient Network for Facial Expression Recognition

An Efficient Expression Recognition Network Based on Gabor Convolution: CSE-GResNet Academic Background Facial Expression Recognition (FER) is an important research direction in the field of computer vision, with wide applications in social robots, healthcare, social psychology, customer service, and psychoanalysis. Facial expressions are natural a...

Phonetically-Anchored Domain Adaptation for Cross-Lingual Speech Emotion Recognition

Phonetic-Anchored Domain Adaptation in Cross-Lingual Speech Emotion Recognition Academic Background Speech Emotion Recognition (SER) has broad application prospects in intelligent agents, social robots, voice assistants, and automated call center systems. With the development of globalization, the demand for cross-lingual SER is increasing. However...

Facial 3D Regional Structural Motion Representation Using Lightweight Point Cloud Networks for Micro-Expression Recognition

3D Regional Structural Motion Representation Using Lightweight Point Cloud Networks for Micro-Expression Recognition Academic Background Micro-expressions (MEs) are brief and subtle facial expressions in human emotional expression, typically lasting between 1⁄25 and 1⁄5 of a second. Due to their spontaneity, rapidity, and difficulty to control, mic...

Multi-scale Hyperbolic Contrastive Learning for Cross-subject EEG Emotion Recognition

Cross-Subject EEG Emotion Recognition Research Based on Multi-Scale Hyperbolic Contrastive Learning Academic Background Electroencephalography (EEG), as a physiological signal, plays an important role in the field of affective computing. Compared with traditional non-physiological cues (such as facial expressions or voice), EEG signals have higher ...

Multimodal Sentiment Analysis with Mutual Information-Based Disentangled Representation Learning

Disentangled Representation Learning in Multimodal Sentiment Analysis Using Mutual Information: An Innovative Study Academic Background With the rapid development of social media, the amount of user-generated multimedia content (such as tweets and videos) has increased dramatically. These multimedia data typically include three modalities: visual (...

Spectro-Temporal Modulations Incorporated Two-Stream Robust Speech Emotion Recognition

Research on Two-Stream Robust Speech Emotion Recognition Based on Spectro-Temporal Modulation Features Academic Background Speech Emotion Recognition (SER) is a technology that identifies emotions by analyzing the emotional content in human speech. It has broad application potential in areas such as human-computer interaction, customer service mana...

An Hα–X-ray Surface-Brightness Correlation for Filaments in Cooling-Flow Clusters

Study on the Hα-X-ray Surface Brightness Correlation of Filamentary Structures in Cooling-Flow Clusters Background Introduction In the large-scale structure of the universe, cooling-flow clusters are a crucial type of celestial system. The cores of these galaxy clusters are typically dominated by massive galaxies (brightest cluster galaxies, BCGs) ...

Compartmentalized dendritic plasticity in the mouse retrosplenial cortex links contextual memories formed close in time

Compartmentalized Dendritic Plasticity in the Mouse Retrosplenial Cortex Links Contextual Memories Formed Close in Time Academic Background Memory formation is a dynamic process where individual memories are stored, updated, and integrated into the framework of other preexisting memories to drive adaptive behavior. Recent studies have shown that th...

Experimental Constraints on the Symmetron Field with a Magnetically Levitated Force Sensor

Experimental Constraints on the Symmetron Field: Breakthrough Research with Magnetically Levitated Force Sensors Academic Background Dark energy is the mysterious force behind the accelerated expansion of the universe, but its essence remains an enigma. To explain the nature of dark energy, scientists have proposed various theories, among which the...