A mixed visual encoding model based on the larger-scale receptive field for human brain activity
S Ma, L Wang, P Chen, R Qin, L Hou, B Yan - Brain Sciences, 2022 - mdpi.com
Research on visual encoding models for functional magnetic resonance imaging derived
from deep neural networks, especially CNN (eg, VGG16), has been developed. However …
from deep neural networks, especially CNN (eg, VGG16), has been developed. However …
Foreground-attention in neural decoding: Guiding Loop-Enc-Dec to reconstruct visual stimulus images from fMRI
K Chen, Y Ma, M Sheng… - 2022 International Joint …, 2022 - ieeexplore.ieee.org
The reconstruction of visual stimulus images from functional Magnetic Resonance Imaging
(fMRI) has received extensive attention in recent years, which provides a possibility to …
(fMRI) has received extensive attention in recent years, which provides a possibility to …
EEG-based Decoding of Selective Visual Attention in Superimposed Videos
Selective attention enables humans to efficiently process visual stimuli by enhancing
important locations or objects and filtering out irrelevant information. Locating visual …
important locations or objects and filtering out irrelevant information. Locating visual …