140 citations · 317 across the 25 of their papers we have counts for
8 papers · 1 filter
NeuralOOD: Improving Out-of-Distribution Generalization Performance with Brain-machine Fusion Learning Framework
Shuangchen Zhao, Changde Du, Hui Li +1
Deep Neural Networks (DNNs) have demonstrated exceptional recognition capabilities in traditional computer vision (CV) tasks. However, existing CV models often suffer a significant…
Identifying the Hierarchical Emotional Areas in the Human Brain Through Information Fusion
Zhongyu Huang, Changde Du, Chaozhuo Li +2
The brain basis of emotion has consistently received widespread attention, attracting a large number of studies to explore this cutting-edge topic. However, the methods employed in…
Human-like object concept representations emerge naturally in multimodal large language models
Changde Du, Kaicheng Fu, Bincheng Wen +10
Understanding how humans conceptualize and categorize natural objects offers critical insights into perception and cognition. With the advent of Large Language Models (LLMs), a key…
Multi-label Class Incremental Emotion Decoding with Augmented Emotional Semantics Learning
Kaicheng Fu, Changde Du, Xiaoyu Chen +2
Emotion decoding plays an important role in affective human-computer interaction. However, previous studies ignored the dynamic real-world scenario, where human experience a blend…
Reverse the auditory processing pathway: Coarse-to-fine audio reconstruction from fMRI
Che Liu, Changde Du, Xiaoyu Chen +1
Drawing inspiration from the hierarchical processing of the human auditory system, which transforms sound from low-level acoustic features to high-level semantic understanding, we…
Open-vocabulary Auditory Neural Decoding Using fMRI-prompted LLM
Xiaoyu Chen, Changde Du, Che Liu +2
Decoding language information from brain signals represents a vital research area within brain-computer interfaces, particularly in the context of deciphering the semantic informat…