140 citations · 317 across the 25 of their papers we have counts for
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eess.SP2022★ 2 cited
Multi-view Multi-label Fine-grained Emotion Decoding from Human Brain Activity
Kaicheng Fu, Changde Du, Shengpei Wang +1
Decoding emotional states from human brain activity plays an important role in brain-computer interfaces. Existing emotion decoding methods still have two main limitations: one is…
cs.CV2022★ 2 cited
Decoding Visual Neural Representations by Multimodal Learning of Brain-Visual-Linguistic Features
Changde Du, Kaicheng Fu, Jinpeng Li +1
Decoding human visual neural representations is a challenging task with great scientific significance in revealing vision-processing mechanisms and developing brain-like intelligen…
cs.NE2022★ 11 cited
Multimodal foundation models are better simulators of the human brain
Haoyu Lu, Qiongyi Zhou, Nanyi Fei +8
Multimodal learning, especially large-scale multimodal pre-training, has developed rapidly over the past few years and led to the greatest advances in artificial intelligence (AI).…