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Simultaneous Super-Resolution and Cross-Modality Synthesis of 3D Medical Images Using Weakly-Supervised Joint Convolutional Sparse Coding
2017
2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
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We propose the weakly-supervised joint convolutional sparse coding to simultaneously solve the problems of super-resolution (SR) and cross-modality image synthesis. ...
Local image neighborhoods are naturally preserved by operating on the whole image domain (as opposed to image patches) and using joint convolutional sparse coding. ...
Brain MRI Super-Resolution For the problem of image SR, we focus on the PD-w subjects of the IXI dataset to compare the proposed WEENIE model with several state-of-the-art SR approaches: sparse coding-based ...
doi:10.1109/cvpr.2017.613
dblp:conf/cvpr/HuangSF17
fatcat:cqvxi334xvgopjoc6gbttph5ve
Simultaneous Super-Resolution and Cross-Modality Synthesis of 3D Medical Images using Weakly-Supervised Joint Convolutional Sparse Coding
[article]
2017
arXiv
pre-print
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We propose the weakly-supervised joint convolutional sparse coding to simultaneously solve the problems of super-resolution (SR) and cross-modality image synthesis. ...
Local image neighborhoods are naturally preserved by operating on the whole image domain (as opposed to image patches) and using joint convolutional sparse coding. ...
Brain MRI Super-Resolution For the problem of image SR, we focus on the PD-w subjects of the IXI dataset to compare the proposed WEENIE model with several state-of-the-art SR approaches: sparse coding-based ...
arXiv:1705.02596v1
fatcat:wiupz3otjrc7tgurg37xprea2y
2020 Index IEEE Transactions on Image Processing Vol. 29
2020
IEEE Transactions on Image Processing
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Art Multimodal Target Detection by Sparse Coding: Application to Paint Loss Detection in Paintings. ...
Chen, Y., +, TIP 2020 3596-3611 Data acquisition Learning to Reconstruct and Understand Indoor Scenes From Sparse Views. ...
doi:10.1109/tip.2020.3046056
fatcat:24m6k2elprf2nfmucbjzhvzk3m
Dynamic network coding of working-memory domains and working-memory processes
2019
Nature Communications
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Here, we use machine-learning to determine how aspects of WM are dynamically coded in the human brain. ...
Contrary to early neuropsychological perspectives, these aspects of WM do not map exclusively to brain areas or processing streams; however, the mappings from that literature form salient features within ...
All custom MATLAB routines and data used to generate the analysis and figures of this paper will be committed upon acceptance for review to the following GitHub: https://github.com/esoreq/WM. ...
doi:10.1038/s41467-019-08840-8
pmid:30804436
pmcid:PMC6389921
fatcat:ucbhuevfrbfybhazluva43ndz4
Learning Robust Data Representation: A Knowledge Flow Perspective
[article]
2020
arXiv
pre-print
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It is always demanding to learn robust visual representation for various learning problems; however, this learning and maintenance process usually suffers from noise, incompleteness or knowledge domain ...
This would benefit AI community from literature review to future direction. ...
The very pioneering work is robust sparse transfer coding, whose idea is to seek domain-invariant sparse coding for both domains and the objective function can be formulated as X−DZ 2 F + γ Z 1 + αR(Z) ...
arXiv:1909.13123v2
fatcat:wll23rkrznejvhzsihc6rwcwve
Neural Representations for Object Perception: Structure, Category, and Adaptive Coding
2011
Annual Review of Neuroscience
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may optimize the object code. ...
Object perception is one of the most remarkable capacities of the primate brain. ...
Successful cross-prediction of responses between runs (Figure 2e ) demonstrates that the adaptive search algorithm converged on the same result from different starting points. ...
doi:10.1146/annurev-neuro-060909-153218
pmid:21438683
fatcat:j6nwnuwy75d4nfnhvvtkky4x3q
GRACE: A Visual Comparison Framework for Integrated Spatial and Non-Spatial Geriatric Data
2013
IEEE Transactions on Visualization and Computer Graphics
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The visual analysis framework blends medical imaging, mathematical analysis and interactive visualization techniques, and includes the adaptation of Sparse Partial Least Squares and iterated Tikhonov Regularization ...
In addition to the domain analysis and design description, we demonstrate the usefulness of this approach on two case studies. ...
Thanks to Sriranjani Mandayam and John Yackovich for an early volume rendering prototype, and to the Pitt Vislab for feedback. ...
doi:10.1109/tvcg.2013.161
pmid:24051859
pmcid:PMC4423600
fatcat:mtnriqquurcwhpiqixnhdcxzxy
Neurogenesis-Inspired Dictionary Learning: Online Model Adaption in a Changing World
[article]
2017
arXiv
pre-print
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in the dentate gyrus of the hippocampus, known to be associated with improved cognitive function and adaptation to new environments. ...
(nonadaptive) online sparse coding of Mairal et al. (2009) in the presence of nonstationary data. ...
As it turns out, the fixed-size ODL approach has difficulties adapting to a new domain in nonstationary settings, when the data in both domains are sparse and, across the domains, the supports (i.e., the ...
arXiv:1701.06106v2
fatcat:ulcgefsabrggzedszxyng532fu
Improving Whole-Brain Neural Decoding of fMRI with Domain Adaptation
[article]
2018
biorxiv/medrxiv
pre-print
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In this paper, we proposed a domain adaptation framework for whole-brain fMRI (DawfMRI) to improve whole-brain neural decoding on target data leveraging pre-existing source data. ...
The results demonstrated that appropriate source domain can help improve neural decoding accuracy for challenging classification tasks. The best-case improvement is 8.94% (from 78.64% to 87.58%). ...
Acknowledgment This work was supported by grants from the UK Engineering and Physi- ...
doi:10.1101/375030
fatcat:c4cbany7bfe4bnzgtbpgvgo4ca
Super-Resolution of Brain MRI Images using Overcomplete Dictionaries and Nonlocal Similarity
2019
IEEE Access
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INDEX TERMS Brain MRI, super-resolution, dictionary, sparse representation, compressed sensing, self-similarity. ...
We use the linear relationship among images in the measurement domain and frequency domain to classify image blocks into smooth, texture, and edge feature blocks in the measurement domain. ...
FIGURE 5 . 5 Comparison of visual results with upscaling factor 2 (brain MRI image from Brainweb).
FIGURE 6 . 6 Comparison of visual results with upscaling factor 2 (brain MRI image from MRT). ...
doi:10.1109/access.2019.2900125
fatcat:4phbyarrzvf4li4a4fomlpehlq
2020 Index IEEE Signal Processing Letters Vol. 27
2020
IEEE Signal Processing Letters
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Restoration of Lossy JPEG-Compressed Brain MR Images Using Cross-Domain Neural Networks. ...
., +, LSP 2020 2009-2013 Restoration of Lossy JPEG-Compressed Brain MR Images Using Cross-Domain Neural Networks. ...
doi:10.1109/lsp.2021.3055468
fatcat:wfdtkv6fmngihjdqultujzv4by
Brain Image Synthesis with Unsupervised Multivariate Canonical CSCℓ_4Net
[article]
2021
arXiv
pre-print
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There is a clear need to go beyond the traditional imaging-dependent process and synthesize anatomically specific target-modality data from a source input. ...
In this paper, we propose to learn dedicated features that cross both intre- and intra-modal variations using a novel CSCℓ_4Net. ...
Motivated by the state-of-the-art domain adaptation works [21, 5] , we cross-transfer both intra-modal and inter-modal features to a high-level projective space to handle the multivariate heterogeneous ...
arXiv:2103.11587v1
fatcat:its7pliaa5g77efer5s3zjhyyu
Associate-3Ddet: Perceptual-to-Conceptual Association for 3D Point Cloud Object Detection
[article]
2020
arXiv
pre-print
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This domain adaptation approach mimics the functionality of the human brain when proceeding object perception. ...
In this paper, we innovatively propose a domain adaptation like approach to enhance the robustness of the feature representation. ...
(c) The perceptual-to-conceptual module (P2C) adapts features from the perceptual domain to the conceptual domain, which mimics the knowledge association and retrieval process in the brain. ...
arXiv:2006.04356v1
fatcat:f6e4wjx365hyndi4aztnmqqzfi
Table of contents
2012
IEEE Transactions on Image Processing
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Tao 284 An Algorithm for the Contextual Adaption of SURF Octave Selection With Good Matching Performance: Best Octaves . ............. .................................................................. ...
Xu (Contents Continued on Back Cover)
(Contents Continued from Front Cover)
Lossy Coding of Images and Video
Mosaicing Edge Strength Filter Based Color Filter Array Interpolation . . . . . . . ...
doi:10.1109/tip.2011.2178726
fatcat:vkwtzivdmjc27ljutlfppeb66y
A universal model of esthetic perception based on the sensory coding of natural stimuli
2008
Spatial Vision
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Moreover, evidence from neurophysiological experiments shows that the visual system uses an efficient (sparse) code to process optimally the statistical properties of natural stimuli. ...
This resonant state is thought to be based on the adaptation of the visual system to natural scenes. ...
The author wishes to thank Lothar Spillmann and Gregor Paul for critical reading of the manuscript and anonymous reviewers for constructive criticism. ...
doi:10.1163/156856808782713780
fatcat:7aqv4eglfbfxllgdsjdwoxnnye
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