no code implementations • 13 May 2023 • Ayelet Heimowitz, Yosi Keller
This work presents an unsupervised and semi-automatic image segmentation approach where we formulate the segmentation as a inference problem based on unary and pairwise assignment probabilities computed using low-level image cues.
no code implementations • 9 Aug 2019 • Ayelet Heimowitz, Joakim andén, Amit Singer
Our method is based on the multi-taper method for power spectral density estimation, which aims to reduce the bias and variance of the estimator.
no code implementations • 28 Jan 2019 • Alexander Jung, Alfred O. Hero III, Alexandru Mara, Saeed Jahromi, Ayelet Heimowitz, Yonina C. Eldar
This lends naturally to learning the labels by total variation (TV) minimization, which we solve by applying a recently proposed primal-dual method for non-smooth convex optimization.
1 code implementation • 1 Feb 2018 • Ayelet Heimowitz, Joakim andén, Amit Singer
Selecting particles from the micrographs is difficult especially for small particles with low contrast.