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pro vyhledávání: '"Gaziv, Guy"'
The visual object category reports of artificial neural networks (ANNs) are notoriously sensitive to tiny, adversarial image perturbations. Because human category reports (aka human percepts) are thought to be insensitive to those same small-norm per
Externí odkaz:
http://arxiv.org/abs/2308.06887
Reconstructing natural videos from fMRI brain recordings is very challenging, for two main reasons: (i) As fMRI data acquisition is difficult, we only have a limited amount of supervised samples, which is not enough to cover the huge space of natural
Externí odkaz:
http://arxiv.org/abs/2206.03544
Autor:
Gaziv, Guy, Irani, Michal
In the past few years, significant advancements were made in reconstruction of observed natural images from fMRI brain recordings using deep-learning tools. Here, for the first time, we show that dense 3D depth maps of observed 2D natural images can
Externí odkaz:
http://arxiv.org/abs/2106.05113
Reconstructing observed images from fMRI brain recordings is challenging. Unfortunately, acquiring sufficient "labeled" pairs of {Image, fMRI} (i.e., images with their corresponding fMRI responses) to span the huge space of natural images is prohibit
Externí odkaz:
http://arxiv.org/abs/1907.02431
Autor:
Gaziv, Guy
The Algonauts challenge requires to construct a multi-subject encoder of images to brain activity. Deep networks such as ResNet-50 and AlexNet trained for image classification are known to produce feature representations along their intermediate stag
Externí odkaz:
http://arxiv.org/abs/1907.01034
Autor:
Gaziv, Guy, Beliy, Roman, Granot, Niv, Hoogi, Assaf, Strappini, Francesca, Golan, Tal, Irani, Michal
Publikováno v:
In NeuroImage 1 July 2022 254
Publikováno v:
PLoS ONE. 1/31/2017, Vol. 12 Issue 1, p1-23. 23p.
Akademický článek
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Publikováno v:
Applied Sciences (2076-3417); Feb2021, Vol. 11 Issue 3, p1108, 230p
This handbook provides thorough, in-depth, and well-focused developments of artificial intelligence (AI), machine learning (ML), deep learning (DL), natural language processing (NLP), cryptography, and blockchain approaches, along with their applicat