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pro vyhledávání: '"Feinstein, Ben"'
Autor:
Garg, Shubhika, Feinstein, Ben, Timnat, Shahar, Batchu, Vishal, Dror, Gideon, Rosenthal, Adi Gerzi, Gulshan, Varun
The increasing intensity and frequency of floods is one of the many consequences of our changing climate. In this work, we explore ML techniques that improve the flood detection module of an operational early flood warning system. Our method exploits
Externí odkaz:
http://arxiv.org/abs/2302.08180
Autor:
Haim, Niv, Feinstein, Ben, Granot, Niv, Shocher, Assaf, Bagon, Shai, Dekel, Tali, Irani, Michal
GANs are able to perform generation and manipulation tasks, trained on a single video. However, these single video GANs require unreasonable amount of time to train on a single video, rendering them almost impractical. In this paper we question the n
Externí odkaz:
http://arxiv.org/abs/2205.05725
Autor:
Haim, Niv, Feinstein, Ben, Granot, Niv, Shocher, Assaf, Bagon, Shai, Dekel, Tali, Irani, Michal
GANs are able to perform generation and manipulation tasks, trained on a single video. However, these single video GANs require unreasonable amount of time to train on a single video, rendering them almost impractical. In this paper we question the n
Externí odkaz:
http://arxiv.org/abs/2109.08591
Single image generative models perform synthesis and manipulation tasks by capturing the distribution of patches within a single image. The classical (pre Deep Learning) prevailing approaches for these tasks are based on an optimization process that
Externí odkaz:
http://arxiv.org/abs/2103.15545
A basic operation in Convolutional Neural Networks (CNNs) is spatial resizing of feature maps. This is done either by strided convolution (donwscaling) or transposed convolution (upscaling). Such operations are limited to a fixed filter moving at pre
Externí odkaz:
http://arxiv.org/abs/2006.11120
Akademický článek
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Publikováno v:
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
Single image generative models perform synthesis and manipulation tasks by capturing the distribution of patches within a single image. The classical (pre Deep Learning) prevailing approaches for these tasks are based on an optimization process that
Autor:
Haim, Niv, Feinstein, Ben, Granot, Niv, Shocher, Assaf, Bagon, Shai, Dekel, Tali, Irani, Michal
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783031197895
European Conference on Computer Vision (ECCV)
Lecture Notes in Computer Science
Lecture Notes in Computer Science-Computer Vision – ECCV 2022
European Conference on Computer Vision (ECCV)
Lecture Notes in Computer Science
Lecture Notes in Computer Science-Computer Vision – ECCV 2022
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::825689c3ff58565409be35e4ea1e43c9
https://doi.org/10.1007/978-3-031-19790-1_30
https://doi.org/10.1007/978-3-031-19790-1_30
Akademický článek
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Akademický článek
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