Brain-conditional multimodal synthesis: A survey and taxonomy
W Mai, J Zhang, P Fang, Z Zhang - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
In the era of Artificial Intelligence Generated Content (AIGC), conditional multimodal
synthesis technologies (eg, text-to-image) are dynamically reshaping the natural content …
synthesis technologies (eg, text-to-image) are dynamically reshaping the natural content …
Dream: Visual decoding from reversing human visual system
In this work we present DREAM, an fMRI-to-image method for reconstructing viewed images
from brain activities, grounded on fundamental knowledge of the human visual system. We …
from brain activities, grounded on fundamental knowledge of the human visual system. We …
Psychometry: An omnifit model for image reconstruction from human brain activity
Reconstructing the viewed images from human brain activity bridges human and computer
vision through the Brain-Computer Interface. The inherent variability in brain function …
vision through the Brain-Computer Interface. The inherent variability in brain function …
Visual decoding and reconstruction via eeg embeddings with guided diffusion
How to decode human vision through neural signals has attracted a long-standing interest in
neuroscience and machine learning. Modern contrastive learning and generative models …
neuroscience and machine learning. Modern contrastive learning and generative models …
Improving deep learning with prior knowledge and cognitive models: A survey on enhancing explainability, adversarial robustness and zero-shot learning
F Mumuni, A Mumuni - Cognitive Systems Research, 2024 - Elsevier
We review current and emerging knowledge-informed and brain-inspired cognitive systems
for realizing adversarial defenses, eXplainable Artificial Intelligence (XAI), and zero-shot or …
for realizing adversarial defenses, eXplainable Artificial Intelligence (XAI), and zero-shot or …
Improving visual image reconstruction from human brain activity using latent diffusion models via multiple decoded inputs
Y Takagi, S Nishimoto - arXiv preprint arXiv:2306.11536, 2023 - arxiv.org
The integration of deep learning and neuroscience has been advancing rapidly, which has
led to improvements in the analysis of brain activity and the understanding of deep learning …
led to improvements in the analysis of brain activity and the understanding of deep learning …
Deep neural networks and brain alignment: Brain encoding and decoding (survey)
Can we obtain insights about the brain using AI models? How is the information in deep
learning models related to brain recordings? Can we improve AI models with the help of …
learning models related to brain recordings? Can we improve AI models with the help of …
fmri-pte: A large-scale fmri pretrained transformer encoder for multi-subject brain activity decoding
The exploration of brain activity and its decoding from fMRI data has been a longstanding
pursuit, driven by its potential applications in brain-computer interfaces, medical diagnostics …
pursuit, driven by its potential applications in brain-computer interfaces, medical diagnostics …
BrainSCUBA: Fine-Grained Natural Language Captions of Visual Cortex Selectivity
Understanding the functional organization of higher visual cortex is a central focus in
neuroscience. Past studies have primarily mapped the visual and semantic selectivity of …
neuroscience. Past studies have primarily mapped the visual and semantic selectivity of …
Dual-Guided Brain Diffusion Model: Natural Image Reconstruction from Human Visual Stimulus fMRI
L Meng, C Yang - Bioengineering, 2023 - mdpi.com
The reconstruction of visual stimuli from fMRI signals, which record brain activity, is a
challenging task with crucial research value in the fields of neuroscience and machine …
challenging task with crucial research value in the fields of neuroscience and machine …