no code implementations • 31 Oct 2022 • Selin Aviyente, Alejandro Frangi, Erik Meijering, Arrate Muñoz-Barrutia, Michael Liebling, Dimitri Van De Ville, Jean-Christophe Olivo-Marin, Jelena Kovačević, Michael Unser
The Bio Image and Signal Processing (BISP) Technical Committee (TC) of the IEEE Signal Processing Society (SPS) promotes activities within the broad technical field of biomedical image and signal processing.
1 code implementation • 29 May 2019 • Rohan Varma, Harlin Lee, Jelena Kovačević, Yuejie Chi
This work studies the denoising of piecewise smooth graph signals that exhibit inhomogeneous levels of smoothness over a graph, where the value at each node can be vector-valued.
1 code implementation • 26 Sep 2018 • Rohan Varma, Jelena Kovačević
In this paper, we extend the sampling theory on graphs by constructing a framework that exploits the structure in product graphs for efficient sampling and recovery of bandlimited graph signals that lie on them.
2 code implementations • 1 Dec 2017 • Antonio Ortega, Pascal Frossard, Jelena Kovačević, José M. F. Moura, Pierre Vandergheynst
Research in Graph Signal Processing (GSP) aims to develop tools for processing data defined on irregular graph domains.
Signal Processing
1 code implementation • 8 Jun 2017 • Sufeng. Niu, Siheng Chen, Hanyu Guo, Colin Targonski, Melissa C. Smith, Jelena Kovačević
GVIN emulates the value iteration algorithm by using a novel graph convolution operator, which enables GVIN to learn and plan on irregular spatial graphs.
no code implementations • 11 Feb 2017 • Siheng Chen, Dong Tian, Chen Feng, Anthony Vetro, Jelena Kovačević
We use a general feature-extraction operator to represent application-dependent features and propose a general reconstruction error to evaluate the quality of resampling.
no code implementations • 16 Dec 2015 • Siheng Chen, Rohan Varma, Aarti Singh, Jelena Kovačević
For each class, we provide an explicit definition of the graph signals and construct a corresponding graph dictionary with desirable properties.
no code implementations • 3 Sep 2015 • Filipe Condessa, José Bioucas-Dias, Carlos Castro, John Ozolek, Jelena Kovačević
We introduce a new supervised algorithm for image classification with rejection using multiscale contextual information.
no code implementations • 21 Jul 2015 • Siheng Chen, Rohan Varma, Aarti Singh, Jelena Kovačević
In this paper, we consider a statistical problem of learning a linear model from noisy samples.
no code implementations • 21 Apr 2015 • Siheng Chen, Rohan Varma, Aarti Singh, Jelena Kovačević
We study signal recovery on graphs based on two sampling strategies: random sampling and experimentally designed sampling.
no code implementations • 26 Nov 2014 • Siheng Chen, Aliaksei Sandryhaila, José M. F. Moura, Jelena Kovačević
We consider the problem of signal recovery on graphs as graphs model data with complex structure as signals on a graph.