activity
20172020
most citedUncertainty driven probabilistic voxel selection for image registration

6 citations · 10 across the 5 of their papers we have counts for

collaborators

17 papers

eess.SP2020

Adaptive filters for the moving target indicator system

Boris N. Oreshkin

Adaptive algorithms belong to an important class of algorithms used in radar target detection to overcome prior uncertainty of interference covariance. The contamination of the emp…

eess.SP2020

Optimization of loading factor preventing target cancellation

Boris N. Oreshkin, Peter A. Bakulev

Adaptive algorithms based on sample matrix inversion belong to an important class of algorithms used in radar target detection to overcome prior uncertainty of interference covaria…

cs.CV20201 cited

Optimization over Random and Gradient Probabilistic Pixel Sampling for Fast, Robust Multi-Resolution Image Registration

Boris N. Oreshkin, Tal Arbel

This paper presents an approach to fast image registration through probabilistic pixel sampling. We propose a practical scheme to leverage the benefits of two state-of-the-art pixe…

cs.CV20206 cited

Uncertainty driven probabilistic voxel selection for image registration

Boris N. Oreshkin, Tal Arbel

This paper presents a novel probabilistic voxel selection strategy for medical image registration in time-sensitive contexts, where the goal is aggressive voxel sampling (e.g. usin…

cs.LG2020

N-BEATS neural network for mid-term electricity load forecasting

Boris N. Oreshkin, Grzegorz Dudek, Paweł Pełka +1

This paper addresses the mid-term electricity load forecasting problem. Solving this problem is necessary for power system operation and planning as well as for negotiating forward…

cs.LG2020

FC-GAGA: Fully Connected Gated Graph Architecture for Spatio-Temporal Traffic Forecasting

Boris N. Oreshkin, Arezou Amini, Lucy Coyle +1

Forecasting of multivariate time-series is an important problem that has applications in traffic management, cellular network configuration, and quantitative finance. A special cas…