Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Hirsch, Roy"'
Autor:
Hirsch, Roy, Goldberger, Jacob
Medical imaging classifiers can achieve high predictive accuracy, but quantifying their uncertainty remains an unresolved challenge, which prevents their deployment in medical clinics. We present an algorithm that can modify any classifier to produce
Externí odkaz:
http://arxiv.org/abs/2408.05037
Autor:
Varshavsky-Hassid, Miri, Hirsch, Roy, Cohen, Regev, Golany, Tomer, Freedman, Daniel, Rivlin, Ehud
The incorporation of Denoising Diffusion Models (DDMs) in the Text-to-Speech (TTS) domain is rising, providing great value in synthesizing high quality speech. Although they exhibit impressive audio quality, the extent of their semantic capabilities
Externí odkaz:
http://arxiv.org/abs/2402.12423
A key element of computer-assisted surgery systems is phase recognition of surgical videos. Existing phase recognition algorithms require frame-wise annotation of a large number of videos, which is time and money consuming. In this work we join conce
Externí odkaz:
http://arxiv.org/abs/2310.17209
Efficient Discovery and Effective Evaluation of Visual Perceptual Similarity: A Benchmark and Beyond
Autor:
Barkan, Oren, Reiss, Tal, Weill, Jonathan, Katz, Ori, Hirsch, Roy, Malkiel, Itzik, Koenigstein, Noam
Visual similarities discovery (VSD) is an important task with broad e-commerce applications. Given an image of a certain object, the goal of VSD is to retrieve images of different objects with high perceptual visual similarity. Although being a highl
Externí odkaz:
http://arxiv.org/abs/2308.14753
Autor:
Hirsch, Roy, Caron, Mathilde, Cohen, Regev, Livne, Amir, Shapiro, Ron, Golany, Tomer, Goldenberg, Roman, Freedman, Daniel, Rivlin, Ehud
Publikováno v:
MICCAI 2023
Self-supervised learning (SSL) has led to important breakthroughs in computer vision by allowing learning from large amounts of unlabeled data. As such, it might have a pivotal role to play in biomedicine where annotating data requires a highly speci
Externí odkaz:
http://arxiv.org/abs/2308.12394
Autor:
Nachmani, Eliya, Levkovitch, Alon, Hirsch, Roy, Salazar, Julian, Asawaroengchai, Chulayuth, Mariooryad, Soroosh, Rivlin, Ehud, Skerry-Ryan, RJ, Ramanovich, Michelle Tadmor
We present Spectron, a novel approach to adapting pre-trained large language models (LLMs) to perform spoken question answering (QA) and speech continuation. By endowing the LLM with a pre-trained speech encoder, our model becomes able to take speech
Externí odkaz:
http://arxiv.org/abs/2305.15255
A major challenge in collaborative filtering methods is how to produce recommendations for cold items (items with no ratings), or integrate cold item into an existing catalog. Over the years, a variety of hybrid recommendation models have been propos
Externí odkaz:
http://arxiv.org/abs/2112.07615