[HTML][HTML] Representation learning of resting state fMRI with variational autoencoder
Resting state functional magnetic resonance imaging (rsfMRI) data exhibits complex but
structured patterns. However, the underlying origins are unclear and entangled in rsfMRI …
structured patterns. However, the underlying origins are unclear and entangled in rsfMRI …
Deep neural network predicts emotional responses of the human brain from functional magnetic resonance imaging
An artificial neural network with multiple hidden layers (known as a deep neural network, or
DNN) was employed as a predictive model (DNN p) for the first time to predict emotional …
DNN) was employed as a predictive model (DNN p) for the first time to predict emotional …
Test–retest reliability of spatial patterns from resting-state functional MRI using the restricted Boltzmann machine and hierarchically organized spatial patterns from the …
Abstract Background Restricted Boltzmann machines (RBMs), including greedy layer-wise
trained RBMs as part of a deep belief network (DBN), have the ability to identify spatial …
trained RBMs as part of a deep belief network (DBN), have the ability to identify spatial …
Exploiting activation based gradient output sparsity to accelerate backpropagation in cnns
Machine/deep-learning (ML/DL) based techniques are emerging as a driving force behind
many cutting-edge technologies, achieving high accuracy on computer vision workloads …
many cutting-edge technologies, achieving high accuracy on computer vision workloads …
Evaluation of weight sparsity regularizion schemes of deep neural networks applied to functional neuroimaging data
The paper presented a systematic evaluation of the weight sparsity regularization schemes
for the deep neural networks applied to the whole brain resting-state functional magnetic …
for the deep neural networks applied to the whole brain resting-state functional magnetic …
Optimizing Deep Learning for Memory and Compute: A joint Algorithm-Architecture Exploration
A Sarma - 2022 - etda.libraries.psu.edu
Deep Learning has been transformational across many disciplines of science and
engineering in the recent past. Areas such as vision, speech and language have been …
engineering in the recent past. Areas such as vision, speech and language have been …
Representation Learning of FMRI Data Using Variational Autoencoder
JH Kim - 2021 - search.proquest.com
Functional imaging data of the brain using Magnetic Resonance Imaging (MRI)–fMRI data
exhibits complex but structured patterns. This fMRI data has opened a new venue for …
exhibits complex but structured patterns. This fMRI data has opened a new venue for …
Dimensionality reduction of brain image features
If the feature number is too large, it causes the curse of the dimensionality problem. In the
pathological brain detection (PBD) system, each feature may have many possible values …
pathological brain detection (PBD) system, each feature may have many possible values …