MindLDM: Reconstruct Visual Stimuli from fMRI Using Latent Diffusion Model-Reference-Cited by-同舟云学术

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MindLDM: Reconstruct Visual Stimuli from fMRI Using Latent Diffusion Model

Published:2024-06-14 Issue: Volume:33 Page:1-6
ISSN:
Container-title:2024 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA)
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Author:

Guo Junhao¹,Yi Chanlin²,Li Fali²,Xu Peng²,Tian Yin³

Affiliation:

1. Chongging University of Posts and Telecommunications,College of Computer Science and Technology,Chongqing,China

2. University of Electronic Science and Technology of China,School of Life Science and Technolog,Chengdu,China

3. Chongging University of Posts and Telecommunications,School of Bioinformatic,Chongqing,China

Funder

Interface

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10586233/10586443/10586647.pdf?arnumber=10586647

Reference34 articles.

1. Deep Neural Networks Reveal a Gradient in the Complexity of Neural Representations across the Ventral Stream

2. Identifying natural images from human brain activity

3. Neural Encoding and Decoding with Deep Learning for Dynamic Natural Vision

4. Mind Reader: Reconstructing complex images from brain activities;Lin,2022

5. Reconstructing Perceptive Images from Brain Activity by Shape-Semantic GAN;Fang,2020

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