activity
20182021
most citedOn the Self-Similarity of Natural Stochastic Textures

2 citations · 2 across the 3 of their papers we have counts for

collaborators

5 papers

eess.SP2021

Distortion measure of spectrograms for classification of respiratory diseases

Jeremy Levy, Alexander Naitsat, Yehoshua Y. Zeevi

A new method for the classification of respiratory diseases is presented. The method is based on a novel class of features, extracted from pulmonary sounds, by parameterizing their…

eess.SP2020

Remote atrial fibrillation burden estimation using deep recurrent neural network

Armand Chocron, Julien Oster, Shany Biton +4

The atrial fibrillation burden (AFB) is defined as the percentage of time spend in atrial fibrillation (AF) over a long enough monitoring period. Recent research has demonstrated t…

cs.CV2019

Texture and Structure Two-view Classification of Images

Samah Khawaled, Michael Zibulevsky, Yehoshua Y. Zeevi

Textural and structural features can be regraded as "two-view" feature sets. Inspired by the recent progress in multi-view learning, we propose a novel two-view classification meth…

cs.CV20192 cited

On the Self-Similarity of Natural Stochastic Textures

Samah Khawaled, Yehoshua Y. Zeevi

Self-similarity is the essence of fractal images and, as such, characterizes natural stochastic textures. This paper is concerned with the property of self-similarity in the statis…

cs.CV2018

Modelling local phase of images and textures with applications in phase denoising and phase retrieval

Ido Zachevsky, Yehoshua Y. Zeevi

The Fourier magnitude has been studied extensively, but less effort has been devoted to the Fourier phase, despite its well-established importance in image representation. Global p…