2 citations · 3 across the 6 of their papers we have counts for
6 papers
E^2-LLM: Bridging Neural Signals and Interpretable Affective Analysis
Fei Ma, Han Lin, Yifan Xie +4
Emotion recognition from electroencephalography (EEG) signals remains challenging due to high inter-subject variability, limited labeled data, and the lack of interpretable reasoni…
Spiking Neural Networks Need High Frequency Information
Yuetong Fang, Deming Zhou, Ziqing Wang +5
Spiking Neural Networks promise brain-inspired and energy-efficient computation by transmitting information through binary (0/1) spikes. Yet, their performance still lags behind th…
Adaptive Calibration: A Unified Conversion Framework of Spiking Neural Network
Ziqing Wang, Yuetong Fang, Jiahang Cao +2
Spiking Neural Networks (SNNs) are seen as an energy-efficient alternative to traditional Artificial Neural Networks (ANNs), but the performance gap remains a challenge. While this…
A Review of Human Emotion Synthesis Based on Generative Technology
Fei Ma, Yukan Li, Yifan Xie +8
Human emotion synthesis is a crucial aspect of affective computing. It involves using computational methods to mimic and convey human emotions through various modalities, with the…
Generative Technology for Human Emotion Recognition: A Scope Review
Fei Ma, Yucheng Yuan, Yifan Xie +6
Affective computing stands at the forefront of artificial intelligence (AI), seeking to imbue machines with the ability to comprehend and respond to human emotions. Central to this…
Adaptive Calibration: A Unified Conversion Framework of Spiking Neural Networks
Ziqing Wang, Yuetong Fang, Jiahang Cao +1
Spiking Neural Networks (SNNs) have emerged as a promising energy-efficient alternative to traditional Artificial Neural Networks (ANNs). Despite this, bridging the performance gap…