Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Davis Gilton"'
Publikováno v:
IEEE Transactions on Computational Imaging. 6:328-343
Many challenging image processing tasks can be described by an ill-posed linear inverse problem: deblurring, deconvolution, inpainting, compressed sensing, and superresolution all lie in this framework. Traditional inverse problem solvers minimize a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::af0b8eecde976be7deebc666bfbe7c45
https://doi.org/10.1109/tci.2019.2948732
https://doi.org/10.1109/tci.2019.2948732
Publikováno v:
2021 IEEE 17th International Conference on eScience (eScience).
Unsupervised fashion of cloud analysis has the significant possibility of exploring massive quantities of satellite cloud imagery to discover unknown cloud patterns that can be relevant to climate change research, free from the assumption of artifici
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0e7a34addff00a8e30ee3a7c1e337760
https://doi.org/10.1109/escience51609.2021.00047
https://doi.org/10.1109/escience51609.2021.00047
Publikováno v:
ISBI
Deep neural networks have been successfully applied to a wide variety of inverse problems arising in biomedical imaging. These networks are often trained using a forward model, which is not only used to generate the training data but is often incorpo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2e51156fcc7ade987ead04743e76d809
https://doi.org/10.1109/isbi48211.2021.9433844
https://doi.org/10.1109/isbi48211.2021.9433844
Advanced satellite-born remote sensing instruments produce high-resolution multi-spectral data for much of the globe at a daily cadence. These datasets open up the possibility of improved understanding of cloud dynamics and feedback, which remain the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::77d935c46b6c3cdf300aad0b05bef10c
http://arxiv.org/abs/2103.04885
http://arxiv.org/abs/2103.04885
Recent efforts on solving inverse problems in imaging via deep neural networks use architectures inspired by a fixed number of iterations of an optimization method. The number of iterations is typically quite small due to difficulties in training net
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::10e75b0f06b9b3e166c190359d7a6ecb
Publikováno v:
CAMSAP
Many modern approaches to image reconstruction are based on learning a regularizer that implicitly encodes a prior over the space of images. For large-scale images common in imaging domains like remote sensing, medical imaging, astronomy, and others,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bfc92cae3948a870dacfda43424c5c73
https://doi.org/10.1109/camsap45676.2019.9022624
https://doi.org/10.1109/camsap45676.2019.9022624
Autor:
Kimberly M. Wingert, Scott W. Ruston, Gene A. Brewer, Visar Berisha, Chris Blais, Corianne Rogalsky, B. Hunter Ball, Beate Peter, Leslie C. Baxter, Davis Gilton, Steven R. Corman
Publikováno v:
Brain and Language. :42-49
The neurobiology of bilingualism is hotly debated. The present study examines whether normalized cortical measurements can be used to reliably classify monolinguals versus bilinguals in a structural MRI dataset of Farsi-English bilinguals and English
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7363545f9b13251f51bfb74a38d30dbb
https://doi.org/10.1016/j.bandl.2018.04.005
https://doi.org/10.1016/j.bandl.2018.04.005
Publikováno v:
DSW
Many challenging image processing tasks can be described by an ill-posed linear inverse problem: deblurring, inpainting, compressed sensing, and superresolution all fit in this framework. Traditional inverse problem solvers minimize a cost function c
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bfe031f1a5c24a5810312bbd03a1eeb8
https://doi.org/10.1109/dsw.2019.8755547
https://doi.org/10.1109/dsw.2019.8755547