Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Dana Weitzner"'
Autor:
Dana Weitzner, Raja Giryes
Publikováno v:
IEEE Open Journal of Signal Processing, Vol 4, Pp 99-107 (2023)
The prominent success of neural networks, mainly in computer vision tasks, is increasingly shadowed by their sensitivity to small, barely perceivable adversarial perturbations in image input. In this article, we aim at explaining this vulnerability t
Externí odkaz:
https://doaj.org/article/077bfdba1dd14b3c9cacb25fc6920192
Autor:
Grey Nearing, Martin Gauch, Daniel Klotz, Frederik Kratzert, Asher Metzger, Guy Shalev, Shlomo Shenzis, Tadele Tekalign, Dana Weitzner, Oren Gilon
Deep learning has become the de facto standard for streamflow simulation. While there are examples of deep learning based streamflow forecast models (e.g., 1-5), the majority of the development and research has been done with hindcast models. The pri
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bead22a5df87f8c7001a9e0cc2e569e3
https://doi.org/10.5194/egusphere-egu23-16974
https://doi.org/10.5194/egusphere-egu23-16974
Autor:
Frederik Kratzert, Martin Gauch, Daniel Klotz, Asher Metzger, Grey Nearing, Guy Shalev, Shlomo Shenzis, Tadele Tekalign, Dana Weitzner, Oren Gilon
The goal of Google’s Flood Forecasting Initiative is to provide timely and actionable flood warnings to everyone, globally. Until recently, Google provided operational flood warnings only for specific partner countries, namely India, Bangladesh, Sr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::92464b7198e9e481fda2646b808254b9
https://doi.org/10.5194/egusphere-egu23-5326
https://doi.org/10.5194/egusphere-egu23-5326
Autor:
Zvika Ben-Haim, Zach Moshe, Moriah Royz, Yuval Levin, Nofar Peled Levi, Frederik Kratzert, Niv Giladi, Hila Noga, Dana Weitzner, Dafi Voloshin, Gregory Begelman, Gideon Dror, Sella Nevo, Shahar Timnat, Yotam Gigi, Liora Yuklea, Ofir Reich, Oren Gilon, Asher Metzger, Guy Shalev, Yossi Matias, Chen Barshai, Adi Gerzi Rosenthal, Vladimir Anisimov, Efrat Morin, Tal Shechter, Grey Nearing, Avinatan Hassidim, Ira Shavitt, Gal Elidan, Ronnie Maor
The operational flood forecasting system by Google was developed to provide accurate real-time flood warnings to agencies and the public, with a focus on riverine floods in large, gauged rivers. It became operational in 2018 and has since expanded ge
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::71a4149b2b83102b65c7ecaeeed7d573
https://doi.org/10.5194/hess-2021-554
https://doi.org/10.5194/hess-2021-554
Autor:
Sella Nevo, Efrat Morin, Adi Gerzi Rosenthal, Asher Metzger, Chen Barshai, Dana Weitzner, Dafi Voloshin, Frederik Kratzert, Gal Elidan, Gideon Dror, Gregory Begelman, Grey Nearing, Guy Shalev, Hila Noga, Ira Shavitt, Liora Yuklea, Moriah Royz, Niv Giladi, Nofar Peled Levi, Ofir Reich, Oren Gilon, Ronnie Maor, Shahar Timnat, Tal Shechter, Vladimir Anisimov, Yotam Gigi, Yuval Levin, Zach Moshe, Zvika Ben-Haim, Avinatan Hassidim, Yossi Matias
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8a9ffa6c756998128c621dc3244cd2e1
https://doi.org/10.5194/hess-2021-554-supplement
https://doi.org/10.5194/hess-2021-554-supplement
Autor:
Raja Giryes, Dana Weitzner
Blind deconvolution and demixing is the problem of reconstructing convolved signals and kernels from the sum of their convolutions. This problem arises in many applications, such as blind MIMO. This work presents a separable approach to blind deconvo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1a27c69a380b1eddb93b6280781961ed
Publikováno v:
ICIP
Face verification is a fast-growing authentication tool for everyday systems, such as smartphones. While current 2D face recognition methods are very accurate, it has been suggested recently that one may wish to add a 3D sensor to such solutions to m
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::58e84ee311e2abbad8e78130651b9474
http://arxiv.org/abs/2006.00473
http://arxiv.org/abs/2006.00473
Autor:
Dana Weitzner, Raja Giryes
Publikováno v:
ICASSP
Blind deconvolution and demixing is the problem of reconstructing convolved signals and kernels from the sum of their convolutions. This problem arises in many applications, such as blind MIMO. In this work, we present a separable approach to blind d
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b8619212fc9ee4c56378a2287e267dc8
https://doi.org/10.1109/icassp40776.2020.9054464
https://doi.org/10.1109/icassp40776.2020.9054464