Deep learning in bioinformatics: Introduction, application, and perspective in the big data era
Deep learning, which is especially formidable in handling big data, has achieved great
success in various fields, including bioinformatics. With the advances of the big data era in …
success in various fields, including bioinformatics. With the advances of the big data era in …
A survey on deep learning-based non-invasive brain signals: recent advances and new frontiers
Brain signals refer to the biometric information collected from the human brain. The research
on brain signals aims to discover the underlying neurological or physical status of the …
on brain signals aims to discover the underlying neurological or physical status of the …
High-resolution image reconstruction with latent diffusion models from human brain activity
Y Takagi, S Nishimoto - … of the IEEE/CVF Conference on …, 2023 - openaccess.thecvf.com
Reconstructing visual experiences from human brain activity offers a unique way to
understand how the brain represents the world, and to interpret the connection between …
understand how the brain represents the world, and to interpret the connection between …
Reconstructing the mind's eye: fMRI-to-image with contrastive learning and diffusion priors
We present MindEye, a novel fMRI-to-image approach to retrieve and reconstruct viewed
images from brain activity. Our model comprises two parallel submodules that are …
images from brain activity. Our model comprises two parallel submodules that are …
Deep image reconstruction from human brain activity
The mental contents of perception and imagery are thought to be encoded in hierarchical
representations in the brain, but previous attempts to visualize perceptual contents have …
representations in the brain, but previous attempts to visualize perceptual contents have …
[HTML][HTML] Protein–protein interaction prediction with deep learning: A comprehensive review
Most proteins perform their biological function by interacting with themselves or other
molecules. Thus, one may obtain biological insights into protein functions, disease …
molecules. Thus, one may obtain biological insights into protein functions, disease …
[HTML][HTML] FA-GAN: Fused attentive generative adversarial networks for MRI image super-resolution
High-resolution magnetic resonance images can provide fine-grained anatomical
information, but acquiring such data requires a long scanning time. In this paper, a …
information, but acquiring such data requires a long scanning time. In this paper, a …
[PDF][PDF] A survey on deep learning based brain computer interface: Recent advances and new frontiers
Brain-Computer Interface (BCI) bridges human's neural world and the outer physical world
by decoding individuals' brain signals into commands recognizable by computer devices …
by decoding individuals' brain signals into commands recognizable by computer devices …
[HTML][HTML] Machine learning and artificial intelligence in neuroscience: A primer for researchers
F Badrulhisham, E Pogatzki-Zahn, D Segelcke… - Brain, Behavior, and …, 2024 - Elsevier
Artificial intelligence (AI) is often used to describe the automation of complex tasks that we
would attribute intelligence to. Machine learning (ML) is commonly understood as a set of …
would attribute intelligence to. Machine learning (ML) is commonly understood as a set of …
[HTML][HTML] End-to-end deep image reconstruction from human brain activity
Deep neural networks (DNNs) have recently been applied successfully to brain decoding
and image reconstruction from functional magnetic resonance imaging (fMRI) activity …
and image reconstruction from functional magnetic resonance imaging (fMRI) activity …